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Paper Citation Record · LEDGER

Large Language Model Agent: A Survey on Methodology, Applications and Challenges

As of 5 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 100 inbound Pith citation observations for arXiv:2503.21460.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2503.21460 v1

Coverage vector

measured 100 of 300 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-22T21:51:34.309870Z

measured 200 of 200 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 100 of 102 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T04:50:32.458596Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 300 outbound references displayed

  • verified exact42
  • verified fuzzy56
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch2

External citation measurements

196
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 5c0a2902-3fb5-4d23-88f2-041c8e816d79 · outbound

This paper cites The rise and potential of large language model based agents: A survey.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges The rise and potential of large language model based agents: A survey

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.339286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:dc1ab2f44d182072acb6736a98aee4cb7ce852fd9d26c7bc51d1052197a98fb3

Observation f089e8aa-a8f3-46ff-b7f2-51a517064a31 · outbound

This paper cites Intelligent agents: Theory and practice.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Intelligent agents: Theory and practice

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.505799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:7e0de7d9fddddb2f7417493e1d336bd1c6df2d8e1bf5a1f16796995a764a449e

Observation 6e7dc34d-5b6b-4718-8bfc-0e818cd0559c · outbound

This paper cites How Reliable are LLMs as Knowledge Bases? Re-thinking Facutality and Consistency.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges How Reliable are LLMs as Knowledge Bases? Re-thinking Facutality and Consistency

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.051123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:fe5e2074a08eeab964ab00fd0d5c31a4c3a79490f93c1fd47cb74b4d0187d780

Observation 99679f59-87dd-44df-8a2e-58781d7c05bb · outbound

This paper cites Non-Vacuous Generalization Bounds for Large Language Models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Non-Vacuous Generalization Bounds for Large Language Models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.726372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:5ef6fec97b1a296ac33d440894ea3272c3db07a4471166a4493d6cb76ce71465

Observation 5447c123-6623-4029-9a7a-1f456eac641f · outbound

This paper cites From multimodal llm to human-level ai: Modality, instruction, reasoning, efficiency and beyond.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges From multimodal llm to human-level ai: Modality, instruction, reasoning, efficiency and beyond

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.373561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:561bc61ddc472d2b4630296d69e6ea006bfc8d9d3252d153bc149d0d63789851

Observation 46e4f14b-5203-4929-bc81-2261922c9353 · outbound

This paper cites Towards Reasoning in Large Language Models: A Survey.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Towards Reasoning in Large Language Models: A Survey

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.080528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:e7ca8437e11f3fbfe4225f5c7faae772e445c62edba0fe64e85b3aa4c26901c4

Observation ade4f0d9-996d-47ba-9d2e-4a0b4eb7296f · outbound

This paper cites Tool-lmm: A large multi-modal model for tool agent learning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Tool-lmm: A large multi-modal model for tool agent learning

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.404448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:da571611ee30cdef96b457f2c63acde95cfc1857f2ae5374c293a77771da1a93

Observation af3eb35c-ff97-4868-b454-3c435b6c15e7 · outbound

This paper cites A Survey on the Memory Mechanism of Large Language Model based Agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A Survey on the Memory Mechanism of Large Language Model based Agents

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.624766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:40c8fb93db8b961b6fe1a1137755237b41d276731ea77375d203085a15f52ba0

Observation de67752b-8b19-4680-8e35-220c0a9f381c · outbound

This paper cites An In-depth Survey of Large Language Model-based Artificial Intelligence Agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges An In-depth Survey of Large Language Model-based Artificial Intelligence Agents

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.311685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:dbdc9af25733b64b8f8363026c42553a427e27b183fa1d61dc985b4a62786115

Observation 49d399ff-1f7f-49dd-ac10-41525b6bb192 · outbound

This paper cites Cognitive architectures for language agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Cognitive architectures for language agents

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.041327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:d56431da2b43ead4312c66d9d62b72ccf3ec9a826ac551fe76b10e8036157a03

Observation 2eb16322-b318-47d4-ac85-bb64d533530f · outbound

This paper cites A Survey on Large Language Model-Based Game Agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A Survey on Large Language Model-Based Game Agents

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-06-09T03:06:57.877360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:09e1e7c814932d5a8d539acc83fb964e53f033505f599743033275b073ffd6c4

Observation a6e9e9cc-3981-461b-a2e5-1af74847a6e6 · outbound

This paper cites A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A Survey on Game Playing Agents and Large Models: Methods, Applications, and Challenges

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.471456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:3c7bb511c351323db16ac040bf62f7ccbc26253c5201a523fe9ab81ab8c209c0

Observation 0a50e5e3-bb4b-45b5-9a2a-d0b4afe95e69 · outbound

This paper cites Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.092020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:efdb1d07cd0e98e0d6c67a24e2004aefbaf1d2cca032596b3aa422c3a0e93605

Observation fe8b59d0-07d6-43c3-9dd1-43979304cfdf · outbound

This paper cites Mobile edge intelligence for large language models: A contemporary survey.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Mobile edge intelligence for large language models: A contemporary survey

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.139148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:534a48235d4dbce1296734380501fef19f70684ec09e837bb0f68d8bf9900ef7

Observation 08012a27-4a3b-4a49-946f-247c7dc6b246 · outbound

This paper cites Agent AI: Surveying the Horizons of Multimodal Interaction.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Agent AI: Surveying the Horizons of Multimodal Interaction

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.645544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:e738ccabebec7ccb0b518da9109ae02a55eb811d1e90860e4038f09196f893b0

Observation 561a9f53-aded-445c-9465-84d146170d26 · outbound

This paper cites Large Model Based Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trends.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Large Model Based Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trends

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.640042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:1ab75a10c10ec238c367e041aee64ec13e8a63c0f123ccd3e795539327c836af

Observation fdceb74f-4132-4c8b-873f-a840082ab8e7 · outbound

This paper cites A survey on large language model based autonomous agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A survey on large language model based autonomous agents

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:10.975220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:bc756df28f8c1a395574edf12eb116d8c6391256e42fc32a1f1abef37d58150f

Observation da7c0d9c-cda6-49f9-912c-f14d7f5524e4 · outbound

This paper cites A survey on llm-based multi-agent systems: workflow, infrastructure, and challenges.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A survey on llm-based multi-agent systems: workflow, infrastructure, and challenges

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.204726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:e62d66d28e7cf76a76556e17d02649c2e663883d7f320120ec9daadd5a395b1b

Observation 4f2255c3-037c-4112-b96b-d50ae1ca2b95 · outbound

This paper cites A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A Review of Prominent Paradigms for LLM-Based Agents: Tool Use (Including RAG), Planning, and Feedback Learning

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.548824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:6beb75d408d6a3f0ada092eabffe55142f201dd34c1793e730b0ea2b60717235

Observation bb9ba310-deb4-4f57-8cbb-46b84a085d0c · outbound

This paper cites A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.217468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:289c3bda5d0df91ac6b6932d3cdf4ab106a9e9ad169162b073c4b78fe9b846e5

Observation 7b6dba5d-5f4c-4a91-9f99-01a3e9982027 · outbound

This paper cites A Survey on Vision-Language-Action Models for Embodied AI.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges A Survey on Vision-Language-Action Models for Embodied AI

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.285331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:565806599bc45ac6e44287b3f72eaa05e593fd46fc1407ee5a5dd4af72a05a86

Observation cc39f168-ccac-4a1d-8750-6b57e00d6e35 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.290064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:9478ff70f5771b56abcae6fc76d0faf3b0e228c1410b6d2939d1c210303c9bd1

Observation 3dae9932-5d99-4081-9a6d-b73dddfe6cbf · outbound

This paper cites The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.750006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:d39aca6929061b18612ec9bc7a9822ceade9b8c09f21fc38c7c43b4d078fe0f7

Observation 9d019a3b-4ca8-4a8c-b2b8-2aae6e4be184 · outbound

This paper cites Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospects

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.099020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:32ef6e820a0fdffb332669552cf71db330e4034cce01cfaaedc85af20a82f90f

Observation f30a56ec-dc18-4e28-9b59-64340252f61d · outbound

This paper cites Camel: Communicative agents for.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Camel: Communicative agents for

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.370269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:7f0d01e982eb18b9231ea0f571ea3cfa4c09f810da4b93664d0d9038d05e58fc

Observation 4a943c36-e5ef-49be-a1cc-70643f6f5bcb · outbound

This paper cites Autogen: Enabling next-gen llm applications via multi- agent conversation.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Autogen: Enabling next-gen llm applications via multi- agent conversation

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.376585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:37ce85f71798ed25d3d5ec2bc0ada2f2e946006519e15160aaecd69e08c9c340

Observation 24502e94-1b17-47e5-81b9-e49f6beee537 · outbound

This paper cites Metagpt: Meta programming for a multi-agent collaborative framework.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Metagpt: Meta programming for a multi-agent collaborative framework

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.418895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:b2185129f0d762c28dbb84c90b344cb2e98cec523e0c357a0f996f70effa3628

Observation 84afec36-ef37-4445-b32d-60a1c411644c · outbound

This paper cites Chatdev: Communicative agents for software development.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Chatdev: Communicative agents for software development

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.407997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:8626b4d5bb2a4306a9d054fe0a6071a7088b1f16377414826d25991a07ef8e62

Observation bff4dc9e-1f14-4bee-b093-627d6046ea71 · outbound

This paper cites AFlow: Automating agentic workflow generation.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges AFlow: Automating agentic workflow generation

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.481902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:c4eb8935398db17667153393a5bad27f13e9bca4a400a45b6fd82b38e14fcd2e

Observation 3f5fc840-2d8a-49d5-9116-8a6107bfad81 · outbound

This paper cites Generative agents: Interactive simulacra of human behavior.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Generative agents: Interactive simulacra of human behavior

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.438175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:715c0d6ed79782d7d0fd01834e7dbae0ae8cdf87735213e404d8ccda8b9ebff5

Observation 9f1d6b2c-1a63-43d8-a8c5-8aae0737b743 · outbound

This paper cites User behavior simulation with large language model-based agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges User behavior simulation with large language model-based agents

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.460417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:5ec56e89a02ffd59df97d7399603fabe9b422cccde8c268245d8639c01420260

Observation 6af41cfa-6d54-44e4-ae77-f0921fd7a950 · outbound

This paper cites Dspy: Compiling declarative language model calls into self-improving pipelines.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Dspy: Compiling declarative language model calls into self-improving pipelines

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.026842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:d885db4d252f5dffa5433c214501d37b56525dd7960030668c8ab738d6058a0d

Observation 4182f2b7-c2f3-43b1-8906-bbe9a9a82554 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges React: Synergizing reasoning and acting in language models

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.022783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:ba98f8e4e39a989ff3e5f31cab7e561ddfab20c327a3049e4fccc83bb10712df

Observation 83dd2862-753a-4ad6-ac2b-0a02b1b0af69 · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Graph of thoughts: Solving elaborate problems with large language models

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.301781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:7f968cd6e8635da2680a6faf982b638022e88d9983ff840f2b0f8488e6dc6f49

Observation 4d188c93-f7f8-4ffa-91b8-d50387969f14 · outbound

This paper cites Voyager: An open-ended embodied agent with large language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Voyager: An open-ended embodied agent with large language models

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.311456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:06a8850b94c9c2eaa087a79a42f5ac498c04ecd28874e262e3abf248de35687d

Observation 186f5924-370c-4b79-8882-a95edf464467 · outbound

This paper cites Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.358925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:82985a252e3888bb83808f82e6b25b5e8533318d3c7e8e343f79cc143d7f4671

Observation 85ba188d-7048-4eb4-b94a-934312e684a0 · outbound

This paper cites Expel: Llm agents are experiential learners.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Expel: Llm agents are experiential learners

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.336363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:2f0813df5ebc9cd1320e8b16e4e3671891f6d67099c12b2910baac9108cfc41a

Observation d68776dd-751d-4234-b10f-ddf6b6dd6a83 · outbound

This paper cites Reflexion: Language agents with verbal reinforcement learning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Reflexion: Language agents with verbal reinforcement learning

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.069035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:12f1b43a79d3ec427f4630a1f711c3ccdbb737bf8c77be191f262b4505a6142b

Observation cc32b7c7-9cfe-40f0-b9c3-41a47f26b0af · outbound

This paper cites Tptu: Task planning and tool usage of large language model-based ai agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Tptu: Task planning and tool usage of large language model-based ai agents

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.071783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:9bb77a9344b83429a04b4cca70f2cd8d382575a2610478a80b97a26651b4051e

Observation ac179143-ce70-468a-9cfb-15a99d41f14f · outbound

This paper cites OpenAgents: An Open Platform for Language Agents in the Wild.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges OpenAgents: An Open Platform for Language Agents in the Wild

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.375775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:3c341bf431d9a80c708b4f1cd9c2dedac10f3cb33069a5fc43cb17383e41cd5c

Observation 57dd0fd2-8e46-4d84-bb11-a4dd2b159c49 · outbound

This paper cites Lego-prover: Neural theorem proving with growing libraries.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Lego-prover: Neural theorem proving with growing libraries

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.084146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:b57dd84b305fca2b4d7c7ea5c52967ba51f014ad0e7876b1636af8f894786e89

Observation fc5f663a-54f6-4470-bf4b-e78e6d5824a5 · outbound

This paper cites Memgpt: Towards llms as operating systems.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Memgpt: Towards llms as operating systems

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.415538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:c0b6d401e527e7856a75e27e141e44332bdc22353c787aa896e368973341ac2a

Observation 7fbd48ff-edab-4a84-a82a-4512c5229ff5 · outbound

This paper cites Retrieval- augmented generation for knowledge-intensive nlp tasks.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Retrieval- augmented generation for knowledge-intensive nlp tasks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.038087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:23dfe37954d6aefb1d86735a39cc1b350b797128c6e9c6e7e55d226603893f63

Observation 3f1fae0e-9121-4d91-94f4-e091eeb5c702 · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.353076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:d793802c4b3fafc30a07184c3f2df4b1eeac1443c8bb8c0ba84cb00b53e1b5cd

Observation b3ea85e7-bcb3-4878-811d-d0ff2adcf55d · outbound

This paper cites Chain of agents: Large language models collaborating on long-context tasks.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Chain of agents: Large language models collaborating on long-context tasks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.088037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:f5f875f0b292363043220237c972c59a5211bef07172215c1312540d907a3012

Observation 00bd238a-91d3-45e3-a630-92769c3087b5 · outbound

This paper cites Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.249915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:4fc90ef92f46a88ac2d547381c6144777f246301adb4c1102820434231d1265d

Observation 6842fc7c-c801-49d1-98a5-cd28efb44de2 · outbound

This paper cites Llatrieval: Llm- verified retrieval for verifiable generation.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Llatrieval: Llm- verified retrieval for verifiable generation

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.080924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:a1e7d602d8a43dee7b42cb6d259e94c391855e5f1a5945279e8a0ebeb96788fe

Observation 88c9ef95-9c29-4833-ac40-7906e69809a7 · outbound

This paper cites Graph-augmented reasoning: Evolving step-by-step knowledge graph retrieval for llm reasoning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Graph-augmented reasoning: Evolving step-by-step knowledge graph retrieval for llm reasoning

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.344007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:3b6f944c5d0e70baf1917b24b88eb611ef18dc9ea76ac4e0ad23c8267b73bf62

Observation 22455c76-da20-44c0-a834-ce83a29c7375 · outbound

This paper cites DeepRAG: Thinking to Retrieve Step by Step for Large Language Models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges DeepRAG: Thinking to Retrieve Step by Step for Large Language Models

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.399187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:d171274ba7aad9046b9e40bd11b4cc5a45d0e163cc0e63da2b27f40d00d1310d

Observation 5fc5e81e-8f18-4865-b6f8-6c8dbc8277d8 · outbound

This paper cites Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.194235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:1b389961a6450bbb5f895b5123ee181fe71a2f21800894e9dea1e25f3dc5b002

Observation e4fda432-d39c-4487-8238-31e19243fef4 · outbound

This paper cites Distributed problem solving and planning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Distributed problem solving and planning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.498432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:bd7c9214ea81cd8b4347ee4f7d3e96c597938899bccc74006ba0bf0408e46dfa

Observation f0ade229-30f9-4974-a4fe-9314a78f2fdb · outbound

This paper cites Chain-of-Discussion: A Multi-Model Framework for Complex Evidence-Based Question Answering.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Chain-of-Discussion: A Multi-Model Framework for Complex Evidence-Based Question Answering

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.020953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:953e013e1b1c64e25277c7da1bfa8c9b3c166ccd2eaf934be96bef13aa6a46f0

Observation 3b1a1420-62da-4e8f-9434-2129f308fffb · outbound

This paper cites Tree-Planner: Efficient Close-loop Task Planning with Large Language Models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Tree-Planner: Efficient Close-loop Task Planning with Large Language Models

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.342172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:847ac4b427d7d263bd41275a5eb2c82bfdd152dbf8e655d74bf5902115177f45

Observation 17efd151-8b57-4745-acd8-46118184b1b1 · outbound

This paper cites Reactree: Hierarchical task planning with dynamic tree expansion using llm agent nodes.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Reactree: Hierarchical task planning with dynamic tree expansion using llm agent nodes

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.347549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:767b986763a9e17c5fe3d8aee03a66835ea15cd8b002f20303b7f22b717df242

Observation 2cf426a0-8b7f-4cc0-a1be-7ffe751e44e2 · outbound

This paper cites Large Language Model Guided Tree-of-Thought.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Large Language Model Guided Tree-of-Thought

Reference 55

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T21:52:10.760105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:3a9b6dbb6ab6bb188da11ca85e1f53d3165de73a66076d19be86c845bdb90c3a

Observation 0b1014c1-1d7d-414e-8d5e-7369117c225a · outbound

This paper cites Rest- mcts*: Llm self-training via process reward guided tree search.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Rest- mcts*: Llm self-training via process reward guided tree search

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.151378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:2b36dfd359990585859327ae1e436ce29a0001de3be8df1dc5acc6b25a375e2b

Observation a5057724-1bd7-4a2b-8369-31df9456b3b4 · outbound

This paper cites LLM-MARS: Large Language Model for Behavior Tree Generation and NLP-enhanced Dialogue in Multi-Agent Robot Systems.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges LLM-MARS: Large Language Model for Behavior Tree Generation and NLP-enhanced Dialogue in Multi-Agent Robot Systems

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.387560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:f00c76109646879769156ab87d6e1cda4b38cdb17ed70d6c4583065ca4e10065

Observation 5eb048b7-718c-473b-938d-baa0269bbe3b · outbound

This paper cites LLM-as-BT-Planner: Leveraging LLMs for Behavior Tree Generation in Robot Task Planning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges LLM-as-BT-Planner: Leveraging LLMs for Behavior Tree Generation in Robot Task Planning

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.188967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:fb888200da7c183f5d54daa080fdfd6ad9298a17eefdded393b10be875688b33

Observation bf58b0cb-e131-4239-8a62-0bdd6c8c86a5 · outbound

This paper cites ConceptAgent: LLM-Driven Precondition Grounding and Tree Search for Robust Task Planning and Execution.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges ConceptAgent: LLM-Driven Precondition Grounding and Tree Search for Robust Task Planning and Execution

Reference 59

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.584552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:4495734a9ff5535c9f7a0dfcfd40ab7d3489401063659d0531cab76c2edf7733

Observation 9dea1a10-d38d-4a98-af44-43b274a4fb3e · outbound

This paper cites Grounding llms for robot task planning using closed-loop state feedback.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Grounding llms for robot task planning using closed-loop state feedback

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.452590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:e933149fb7f03baf1d437d42141e0d2718181d0c63b58280122db12bcc045cb6

Observation 5520bb3f-8c4a-41ba-9edc-121492b60a72 · outbound

This paper cites TrainerAgent: Customizable and Efficient Model Training through LLM-Powered Multi-Agent System.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges TrainerAgent: Customizable and Efficient Model Training through LLM-Powered Multi-Agent System

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.305336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:c454144bcd52b7c9c64e7402d93edd966b200c71811285f96415a1f8a888f6e4

Observation 25f22382-a231-4383-9203-1dacc72a3970 · outbound

This paper cites Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM Sampling

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.133995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:2ed560a50d4034e0b7bdbc38cada2a00ca227331b4bd782ecf41aacdd15e70a2

Observation 98f3cf91-3237-4a33-b660-24ddca08ba21 · outbound

This paper cites REVECA: Adaptive Planning and Trajectory-based Validation in Cooperative Language Agents using Information Relevance and Relative Proximity.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges REVECA: Adaptive Planning and Trajectory-based Validation in Cooperative Language Agents using Information Relevance and Relative Proximity

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.707103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:b600c3b8298390ebd65c4424a5c5077c297b0cc0d670d15cd439057d534c11bb

Observation 38077096-b665-42d3-9179-b5f97639c529 · outbound

This paper cites Adaplan- ner: Adaptive planning from feedback with language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Adaplan- ner: Adaptive planning from feedback with language models

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.263283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:76c9f3adf02f91474add7ae2cc5461b1f6a2089a01067db982ad2f5541485083

Observation 76f5509e-fb3e-4831-bd40-b653e53404c0 · outbound

This paper cites Adaptive iterative feedback prompting for obstacle-aware path planning via llms.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Adaptive iterative feedback prompting for obstacle-aware path planning via llms

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.269176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:58f06b04171dd76e17eae4af3b6d43b7c4f4679977dd9e66307dabb1af4141f0

Observation 64824b64-86ad-4761-87e7-17e6ef477f75 · outbound

This paper cites Making Language Models Better Tool Learners with Execution Feedback.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Making Language Models Better Tool Learners with Execution Feedback

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.026782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:c10716db5a1e9d9e62859712807596eccef0b6c0c20c4a5c3858248364a9f541

Observation e6e029a4-4a4f-434b-a962-e359cf5e3662 · outbound

This paper cites Gpt4tools: Teaching large language model to use tools via self- instruction.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Gpt4tools: Teaching large language model to use tools via self- instruction

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.453539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:4ff8c01c3798c90603a56a4b6ca80e84f6b2592f81adea88d4501597e22d3330

Observation 1952bb70-6a4a-416c-b542-a18bc9d32576 · outbound

This paper cites EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.392934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:e01fb9cd7ef43fc92a06ae8b0ff046268ca78ce5ed60ac6404e6dcdf792a8264

Observation 73ecf9ed-935c-426f-8448-81b88f811222 · outbound

This paper cites Avatar: Optimizing llm agents for tool usage via contrastive reasoning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Avatar: Optimizing llm agents for tool usage via contrastive reasoning

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.221615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:b407f977df2e687cd07aec518db2c3b451747ad20894029c633dbc5f6d15c15d

Observation 6e26ae4a-4046-4b09-a748-cf25951dd5c0 · outbound

This paper cites Drivlme: Enhancing llm-based autonomous driving agents with embodied and social experiences.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Drivlme: Enhancing llm-based autonomous driving agents with embodied and social experiences

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.184232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:b67f7b88c56fd308eb05964f0be1b2db4ed395e5afb818bde1adefaee600991d

Observation 0462b9e0-5d4c-451f-a9f9-92ab178012bc · outbound

This paper cites Towards efficient llm grounding for embodied multi-agent collab- oration.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Towards efficient llm grounding for embodied multi-agent collab- oration

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.364739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:2cf320e22200b61c9abb1031835242d7b3482d55259b3345615595c76a0eade0

Observation b4d36180-fe66-4839-9f4e-c3f152e80d4e · outbound

This paper cites Improving embodied llm agents capabilities through collaboration.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Improving embodied llm agents capabilities through collaboration

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.198731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:9f21fdabbd9d542837c680971fd833623f511a84285be87a2471cd2e77103e6c

Observation 1fef346c-dc49-4630-a097-1880ce93af1f · outbound

This paper cites Autonomous chemical research with large language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Autonomous chemical research with large language models

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.217669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:512781a81e4b03622f5c011bb65f8ed045a15021ccf35e1f6d7e05581a372bfe

Observation 36101313-4840-4496-98ea-af4757273c81 · outbound

This paper cites Llmlingua: Compressing prompts for accelerated inference of large language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Llmlingua: Compressing prompts for accelerated inference of large language models

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.289474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:6c826d10c56d2ecb98515fc65b4c8280022acb8cdc4b991fb632832858543e00

Observation 6d4f4221-62d5-41c3-9b03-30186a123e27 · outbound

This paper cites AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planning

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.116682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:8fc7133fe13014be832e1d0d893e8bfacdd670dec7e0d6b04dcd381dd3d813f0

Observation bcbc2671-1924-4e4c-930b-b1aeea554dce · outbound

This paper cites Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding

Reference 76

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.295235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:83a038db3e7050ba06afc7876cbc6d93a48eb3ca5a796d87a45658506597ac40

Observation e6b59651-460d-4233-b41f-f1075e6cf072 · outbound

This paper cites Debating with More Persuasive LLMs Leads to More Truthful Answers.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Debating with More Persuasive LLMs Leads to More Truthful Answers

Reference 77

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T21:52:10.426826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:9fcf4800dbe1dcceaad6dfff128e244a7fa1d98bb1df7ac1a5c4c8d3609cbbf8

Observation a7f31c62-c311-474e-a103-f30101371211 · outbound

This paper cites MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning

Reference 78

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.172344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:afb5f993ed8a7514715957a2e64592470f408f8cac96aa9ceb71b46edaf86e4c

Observation d64a3621-d759-4ed1-879c-5a98e616434d · outbound

This paper cites ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs

Reference 79

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.437437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:01efeca4e24724a15b624ba19da0dbf70c458b4ecfe357406f1ddeacb26be9c0

Observation 3e7ff025-e3f5-4fee-ae7e-381902c118f9 · outbound

This paper cites Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Reference 80

Resolution
verified exact
local_arxiv, observed 2026-05-22T21:52:10.575611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:f2b95329e872bfde95c65a15da7831cbbd1f600cb0b29ca421160b9797f3eec5

Observation d4360884-1e60-4b85-87b2-3f79429a9667 · outbound

This paper cites Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.147985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:1920db2f5f76877b2d6cfcaa13db86926acd280e9c025481371b94de457bbe90

Observation bcd41c03-3771-48c1-baf2-c60c71fa4708 · outbound

This paper cites Improving factuality and reasoning in language models through multiagent debate.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Improving factuality and reasoning in language models through multiagent debate

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.509090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:8f844e33fab936e8f80748767f26414ee7e99ba5c99abc3a309f1399ff3ca251

Observation 2253c9a4-9c51-402a-9b7c-62b16618c21f · outbound

This paper cites KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents

Reference 83

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.300142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:29ed39f199962c74c29ff687c48180f8df9e6f9a1406167e4daf9d2affbc7f01

Observation 1dd83f43-2020-4d30-80ff-5a70d1acd13d · outbound

This paper cites Agent planning with world knowledge model.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Agent planning with world knowledge model

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.142210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:c66debe71773e40af3465f98c087cec700a6bb41108b6b9d2d1f5b4dc7fca5ca

Observation 83d293da-7c1b-48e4-83d6-c81418aaf170 · outbound

This paper cites Refining guideline knowledge for agent planning using textgrad.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Refining guideline knowledge for agent planning using textgrad

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.047643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:a0a34c8514ee7b66646777bbc73cdfc1f5946feeb7984f8ffc4b940f3b9173fc

Observation 64a9ef6c-ea63-441c-bb73-83ce73ed318b · outbound

This paper cites Self-evolution learning for discriminative language model pretraining.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Self-evolution learning for discriminative language model pretraining

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.457169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:5bb9bfe2b913a7a5a8c66c100670c0cc896d89fbf557c37e7389cf6f77e0abd6

Observation 369f05be-0247-4821-bcc5-0d9b595a94d9 · outbound

This paper cites Evolutionary op- timization of model merging recipes.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Evolutionary op- timization of model merging recipes

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.463877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:65003e7095404cf28a9d7153ce6d2f47662fbbcb1450ff9804b0df30bd407352

Observation b9297f4f-b6dd-4f5f-bbbb-21083cfbbe58 · outbound

This paper cites Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning

Reference 88

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.087202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:ebdd7a00f46e64102b2cbaa0b5d651b039ef0e377d6e32e8cfce14c0f28247e7

Observation e7058a77-ecc7-41ee-8f66-e4e7450a75b8 · outbound

This paper cites Self-refine: Iterative refinement with self-feedback.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Self-refine: Iterative refinement with self-feedback

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.394718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:03da8d9493b14f4a0ffb3fcc7853c350f18daab3b233c3267f49a03308241d1d

Observation 0da2e8b3-ade0-4aa5-bbcf-14f0defaaf7c · outbound

This paper cites Star: Self-taught reasoner bootstrapping reasoning with reasoning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Star: Self-taught reasoner bootstrapping reasoning with reasoning

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.325878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:8d8b330cfa22e66b3b65fe14f477d551227e8034adae0dced6ebaade95b00fdc

Observation ce34bae5-1e50-4bff-b0bd-cef0ed155401 · outbound

This paper cites V-star: Training verifiers for self-taught reasoners.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges V-star: Training verifiers for self-taught reasoners

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.352024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:29afbe983edd71d40cb2be48137653b5ab9fe6c3e4080dad8f01f612381541be

Observation d37dbfd5-9d86-4b3b-b1b1-259066f36f03 · outbound

This paper cites Large language models are better reasoners with self-verification.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Large language models are better reasoners with self-verification

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.363764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:0524305eb87147ff4c94e6118e51b0d3659deeb10c8311874cd084126906c14f

Observation 71dfd3ef-5b99-488d-9251-6293fd8551d4 · outbound

This paper cites Self-rewarding language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Self-rewarding language models

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.488205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:1adb23e20080c9aab38b796001ba6c4c3e2709f6163331222aca1a628775f580

Observation ccee8e5b-ed3b-486e-9917-69302ab5e3cb · outbound

This paper cites Rlcd: Reinforcement learning from contrastive distillation for lm align- ment.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Rlcd: Reinforcement learning from contrastive distillation for lm align- ment

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.304932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:bfe12abafc8e3ea2a315ff711427735eb6993fd59bc712a02bcee61cb298aee4

Observation 6b90f657-643a-4752-a8c5-084bdf456323 · outbound

This paper cites Language model self-improvement by reinforcement learning contemplation.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Language model self-improvement by reinforcement learning contemplation

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.239888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:1dff201d57c4ce0e1c2978f6bef0f69ce38784f2c842c80a39053b82b8bf1481

Observation d2885d72-fe76-45a8-9f86-be2975eb1a1e · outbound

This paper cites Proagent: building proactive cooperative agents with large language models.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Proagent: building proactive cooperative agents with large language models

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.227673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:0501a8978f5734bbbf55c70875a5c0dc0f1e703c3cac2cf7f1c1c3a0930556a0

Observation 0a990d47-2ec1-491c-a9e0-450a89d6ca1c · outbound

This paper cites Coevolving with the other you: Fine-tuning llm with sequential cooperative multi-agent reinforcement learning.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Coevolving with the other you: Fine-tuning llm with sequential cooperative multi-agent reinforcement learning

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:10.971981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:bf8bafc89f31bf7c50ea42392ab3895791e6aca93ea3ba11fb6a93241e8c696c

Observation 87af85e8-86d9-4b9b-b901-e41e9b12a763 · outbound

This paper cites Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Evolving Diverse Red-team Language Models in Multi-round Multi-agent Games

Reference 98

Resolution
verified exact
arxiv_id, observed 2026-05-22T21:52:10.504270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:1b550e6fa7b167bcd27b41352714fcee54ca918a72cb284ccd5ffaf2b9dc4f58

Observation 788daf70-f775-44af-bf9a-43ab96372c90 · outbound

This paper cites Encouraging divergent thinking in large language models through multi-agent debate.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Encouraging divergent thinking in large language models through multi-agent debate

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.019537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:f57e7364cfeca8910a423225b0f673e84d7739870e99b5b19292bf66c58d8232

Observation d858a511-587e-405a-a043-fad2cf295bb6 · outbound

This paper cites Critic: Large language models can self-correct with tool-interactive critiquing.

Large Language Model Agent: A Survey on Methodology, Applications and Challenges Critic: Large language models can self-correct with tool-interactive critiquing

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-05-22T21:52:11.332113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-22T21:51:34.309870Z digest=sha256:847e03a15ceabd3855da2d52498ee8c8c72cbe594a15c6d94162c417711ba4c4

Pith citing papers

Observation db45686c-97a3-40bd-9475-decadcd666be · inbound

Small Language Models are the Future of Agentic AI cites this paper.

Small Language Models are the Future of Agentic AI Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 50

Resolution
verified exact
local_arxiv, observed 2026-05-16T11:55:51.011936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T11:55:50.897500Z digest=sha256:a15b318b714d1fa4ee8fa3c666ce393ed58889e2878749504d6cb3aa37d92214

Observation ac595254-8265-431c-b400-c9d756d1a477 · inbound

What Factors Affect LLMs and RLLMs in Financial Question Answering? cites this paper.

What Factors Affect LLMs and RLLMs in Financial Question Answering? Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 9

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verified exact
local_arxiv, observed 2026-05-19T05:07:04.497135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-19T05:06:43.406540Z digest=sha256:3d9a7bac6671f9b5ee45ebbdd8a04a4a785f23d654a27e073559a1e4103884de

Observation cc284fdc-decd-4222-9ecd-6c6fd5b7dd91 · inbound

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 19

Resolution
metadata mismatch
local_arxiv, observed 2026-05-18T19:21:46.673527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-18T19:19:36.427337Z digest=sha256:0f4f49ce76c789bd5f79e20e2edf4533195ae5748e5d25ef06796f2c7e7f6e9d

Observation d1f74be9-4591-44e8-97ac-58a2fa34372a · inbound

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial cites this paper.

Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 249

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unresolved
no resolver link, observed 2026-08-05T04:50:32.458596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T04:50:32.458596Z digest=sha256:1b1be9d0b69df85e83d1512e487d0ef65d794c02e1edbb5034393318b80e14d3

Observation 6d55aed8-a616-449d-bc83-3e54216e70a3 · inbound

Free-MAD: Consensus-Free Multi-Agent Debate cites this paper.

Free-MAD: Consensus-Free Multi-Agent Debate Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 6

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unresolved
no resolver link, observed 2026-08-04T17:14:59.774813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:14:59.774813Z digest=sha256:f2795f764424c862d6476fbc5036f2574e595d2b9a8e4429868b42945210fbdb

Observation 373b828f-2086-4778-8a7d-8f54c1bb918c · inbound

Tractable Asymmetric Verification for Large Language Models via Deterministic Replicability cites this paper.

Tractable Asymmetric Verification for Large Language Models via Deterministic Replicability Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T17:10:42.733548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:10:42.733548Z digest=sha256:2eebe66648679726a5801ac726fe4a6ea0ee3624ec7e0d498f0dc61e43b39ca9

Observation 4fe99f06-6490-4723-81ba-f0ba4c490e0b · inbound

GenCellAgent: Generalizable, Training-Free Cellular Image Segmentation via Large Language Model Agents cites this paper.

GenCellAgent: Generalizable, Training-Free Cellular Image Segmentation via Large Language Model Agents Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 29

Resolution
metadata mismatch
local_arxiv, observed 2026-05-18T07:26:03.469486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-18T07:22:58.072356Z digest=sha256:d057c40e51e5e7163c743fba4fe54059293535b37b30ae091002806ce90c142a

Observation 50954a94-acc2-47a8-8bcf-0c9f3dcb80bc · inbound

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle cites this paper.

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-18T06:20:58.359294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-18T06:19:44.360734Z digest=sha256:9248499c59b010099c5aa8a3b6d8108afe45e379e286ad28ddda9596e47c4043

Observation a61a3a8c-a8c4-4ebc-a8fd-4557393d82ce · inbound

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle cites this paper.

EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-21T20:50:36.475045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-21T20:50:06.642976Z digest=sha256:94d978fc470fd63b31bb12818c6db738f3775c19a16407a772b164bf8a0c50fb

Observation ebecd0ab-3c1f-42ef-9cb3-8c07e6d0c7ae · inbound

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts cites this paper.

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-18T04:25:52.264979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-18T04:22:54.943043Z digest=sha256:3b5dc5beaa650714d01986ce462a8b26a817bfe642104ef1c56f664c00e4e0b6

Observation bf3e89d1-0ac0-4a50-8683-b6912acf62e0 · inbound

Graph-Enhanced Policy Optimization in LLM Agent Training cites this paper.

Graph-Enhanced Policy Optimization in LLM Agent Training Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T07:17:44.618432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:17:44.618432Z digest=sha256:c559b46851d245e9e0cdecc01be4a2ef9509be58f75a0b9cd92285e621c84955

Observation bcd3e2e9-ed4b-4250-812f-4c26a40b2a25 · inbound

SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs cites this paper.

SEAL: Self-Evolving Agentic Learning for Conversational Question Answering over Knowledge Graphs Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 58

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unresolved
no resolver link, observed 2026-08-03T18:33:56.262137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:33:56.262137Z digest=sha256:2cb1ced7a904991a69ed4c932e6da584ddc240af287cff0766b77e3c567c3795

Observation ceda2b83-00e2-4720-9b64-803734c17d9b · inbound

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding cites this paper.

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-05-25T07:05:26.475962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-25T07:05:21.138206Z digest=sha256:e836cfff56edc221e738536e03aab602753c27c325fb1be95ad104e99854875f

Observation 0a449cd0-65c1-4fa2-aea6-660347d51d6e · inbound

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding cites this paper.

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 37

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unresolved
no resolver link, observed 2026-08-03T09:44:01.534244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T09:44:01.534244Z digest=sha256:89fc33d36b6a4686c918f29b72ba0d69db5c6039a3d04a97d930146e2abbafd3

Observation c56feb7c-dc0c-4e6d-841d-dbebc59013f4 · inbound

MemOCR: Layout-Aware Visual Memory for Efficient Long-Horizon Reasoning cites this paper.

MemOCR: Layout-Aware Visual Memory for Efficient Long-Horizon Reasoning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-05-21T15:20:17.531365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-21T15:15:22.055616Z digest=sha256:58029270df0b594bc5c4b7de6714a11b2e489338383c1c180b1d32a7bf5fca66

Observation f63579cd-6778-4ea6-81ea-4af5768bb23d · inbound

WorldCup Sampling for Multi-bit LLM Watermarking cites this paper.

WorldCup Sampling for Multi-bit LLM Watermarking Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 6

Resolution
metadata mismatch
local_arxiv, observed 2026-05-16T08:37:36.878470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-11T11:50:26.030339Z digest=sha256:23d4121bab0a3fbb5a542df8d6c5caa1a5ac601fdb03a0d85af1c520c1802972

Observation d340c161-3264-444a-9f52-57085f0406ad · inbound

When control meets large language models: From words to dynamics cites this paper.

When control meets large language models: From words to dynamics Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-05-21T14:54:13.068228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-21T14:52:44.632671Z digest=sha256:a4c2baec16b8f06869e2a6c15256cf3e70f7f80a1d1107d883fa736c1558e4c3

Observation b1c54076-50bf-4ebe-aace-c3a47bbc63c1 · inbound

SupChain-Bench: Benchmarking Large Language Models for Real-World Supply Chain Management cites this paper.

SupChain-Bench: Benchmarking Large Language Models for Real-World Supply Chain Management Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 2

Resolution
metadata mismatch
local_arxiv, observed 2026-05-16T06:50:42.254113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T06:49:38.930482Z digest=sha256:d885163b0585554e73fb8a4c691e57de07c9a6f8244ae16ce0024d01cd1318ee

Observation bea59db8-b3f3-45ce-a390-c1d23d7dfc72 · inbound

Linguistics and Human Brain: A Perspective of Computational Neuroscience cites this paper.

Linguistics and Human Brain: A Perspective of Computational Neuroscience Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 161

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no resolver link, observed 2026-08-03T03:22:46.140300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:22:46.140300Z digest=sha256:4b5ce9aa76fa0091821dc9e3891ac7c9af8a997834cec8fab4a81e55967585be

Observation 58076f70-734f-4534-9d21-03ec95fa45c5 · inbound

EcoGym: Evaluating LLMs for Long-Horizon Plan-and-Execute in Interactive Economies cites this paper.

EcoGym: Evaluating LLMs for Long-Horizon Plan-and-Execute in Interactive Economies Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-05-16T05:57:24.582632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T05:53:29.860037Z digest=sha256:74f3a86b2a04640cc92ce7dc52d619c46ee2b9f595d39ed3095ff3cdb77c9a6a

Observation 92f7b636-3a96-4469-a02a-e29c7c8c4c59 · inbound

Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP cites this paper.

Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-16T05:07:20.637001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-16T05:05:16.370606Z digest=sha256:072ef848f4c03d70d629f366169dca3a86f09c97683bdb9eb15c90725e818211

Observation dfb81d1e-46b9-4122-89bf-649e9850b347 · inbound

Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward cites this paper.

Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 5

Resolution
verified exact
local_arxiv, observed 2026-05-13T07:39:45.427617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-13T07:39:45.272421Z digest=sha256:874964271c32c193ccce6ed7e202ee4c7fc99987e38a9de5e599c3a44924ca30

Observation bcda1c5b-506a-45cf-83fd-966e9c91927f · inbound

Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward cites this paper.

Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-02T23:50:44.271822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T23:50:44.271822Z digest=sha256:2cda038392f6d36ba5801f49e0df0574c8e1d59aa451469fa14eab8f7c7120f8

Observation 8e927024-0fb4-4843-a37e-1b78f37cd06c · inbound

Agent Skill Framework: Perspectives on the Potential of Small to Medium Language Models in Industrial Environments cites this paper.

Agent Skill Framework: Perspectives on the Potential of Small to Medium Language Models in Industrial Environments Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-02T22:29:31.162903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:29:31.162903Z digest=sha256:0938b7bb32c0453756d27c2791a8517511f88a3a63c7d0f577440964f8e879e0

Observation 15a12664-004c-4515-a3a0-63e549c9cfe7 · inbound

From Leaky Thoughts to Private Reasoning: Controlling What LRMs Say to Themselves cites this paper.

From Leaky Thoughts to Private Reasoning: Controlling What LRMs Say to Themselves Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 5

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unresolved
no resolver link, observed 2026-08-02T20:20:41.251027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:20:41.251027Z digest=sha256:3f9853ff40ebb97b6c4caf72c8b0c7888863d544c825ee9a8255a0f4c1d3a056

Observation 8d59d114-94f8-4af7-b6f2-5e0297eefe16 · inbound

Position: Modular Memory is the Key to Continual Learning Agents cites this paper.

Position: Modular Memory is the Key to Continual Learning Agents Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 30

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unresolved
no resolver link, observed 2026-08-02T19:33:04.527652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:33:04.527652Z digest=sha256:541365888b204ad9d65360d18d1e0ba4992a79b7e525cb6d847ff62ed20f4762

Observation f6aba4d5-afaa-4a7a-ba3f-4118d301f310 · inbound

Chain-of-Authorization: Embedding authorization into large language models cites this paper.

Chain-of-Authorization: Embedding authorization into large language models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-05-15T01:13:25.977827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T01:12:46.808187Z digest=sha256:bef5e89bde33a8e849e2969308015af3b5f50300c896ffffa1615c1e45846525

Observation 5bc366bc-81b8-41ec-b20b-f68aa65e4086 · inbound

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering cites this paper.

Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 94

Resolution
metadata mismatch
local_arxiv, observed 2026-05-10T17:40:39.817967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-10T17:40:14.733882Z digest=sha256:14ded22df6a4673bc595dd9f14387c2d148426ef06f2b669b5c2796ce1c38a38

Observation 48ea064b-b290-4278-be4a-60130b52ec22 · inbound

Skill-Conditioned Visual Geolocation for Vision-Language Models cites this paper.

Skill-Conditioned Visual Geolocation for Vision-Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-05-11T06:01:02.334306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T17:49:50.853502Z digest=sha256:29d5fb8837f0e26d4cd6c799b803aca7a32b2ad26820cd79e3f436c8f79eff7b

Observation a1447e4c-1cf3-48b4-9e27-33b5dc51811a · inbound

Skill-Conditioned Visual Geolocation for Vision-Language Models cites this paper.

Skill-Conditioned Visual Geolocation for Vision-Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-05-14T22:03:02.457646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-14T22:02:21.638064Z digest=sha256:1cbf8b98b65f510489cb403f2dd46b4bb85263177e3ee17340a7c7a1e1b8419e

Observation 971cbe23-4038-4813-bca2-c35b33ba0eb7 · inbound

WaterAdmin: Orchestrating Community Water Distribution Optimization via AI Agents cites this paper.

WaterAdmin: Orchestrating Community Water Distribution Optimization via AI Agents Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-05-11T10:06:05.705834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T15:38:00.686435Z digest=sha256:638f6ffb9930047d65a65b5b0cc0bc2755fbb4bfb75335db54b9c73334ca0657

Observation 37b481ba-72a6-4fcf-a903-2ad0a00c497a · inbound

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images cites this paper.

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-11T08:26:01.547584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T16:38:11.785469Z digest=sha256:c6dd024c898ed7c6ce5f058538b5f512a5877c68433961c052c76b7f729045a3

Observation 73aeba5e-4857-48a9-abed-ee8840cd270b · inbound

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images cites this paper.

Test-time Scaling over Perception: Resolving the Grounding Paradox in Thinking with Images Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T05:31:42.808143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:31:42.808143Z digest=sha256:1b61898d811d83f47f1e79faa0a00172943315ed3321df93aa1a83e0da28480e

Observation 5d65bd75-ed44-43d2-bf3f-3fe4fac7e3f4 · inbound

Red Skills or Blue Skills? A Dive Into Skills Published on ClawHub cites this paper.

Red Skills or Blue Skills? A Dive Into Skills Published on ClawHub Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-05-15T08:35:18.560032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T08:33:53.625397Z digest=sha256:c7fb8fd01407d68445c57c04cd23c8ee07afa46bcd108c6270311fff18a27d5d

Observation 50e66032-7e7e-43db-bef0-157cd2d2379d · inbound

CogEvolution: A Human-like Generative Educational Agent to Simulate Student's Cognitive Evolution cites this paper.

CogEvolution: A Human-like Generative Educational Agent to Simulate Student's Cognitive Evolution Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-10T10:49:55.172957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-11T11:50:26.030339Z digest=sha256:f49d76d70e0c993d5d4ac6899b65f25cd0cf5df7e286b5104e1cb3e941ecd11b

Observation 60929441-f50c-4ca3-812c-4f5dd707001f · inbound

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation cites this paper.

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-10T08:12:26.720544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-10T08:09:33.593992Z digest=sha256:fd268843ab17ae9d6c4786e044661e5dca2fd38b88989f9d7fc2ef1271d92eb7

Observation cbb73410-734e-4a20-9515-d103f68ea26b · inbound

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation cites this paper.

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 18

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verified exact
local_arxiv, observed 2026-07-06T07:22:04.625351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-06T07:16:02.873020Z digest=sha256:37b9dfc021365e9cbff36ee3ce5c92080658d4f4d6e27c449aef332c7e441eb7

Observation ea0fbf3e-259c-4a58-a1df-b64565b741b8 · inbound

SafetyALFRED: Evaluating Safety-Conscious Planning of Multimodal Large Language Models cites this paper.

SafetyALFRED: Evaluating Safety-Conscious Planning of Multimodal Large Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 32

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T13:06:04.405561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-10T02:21:29.463149Z digest=sha256:1d8179534f66a1a2565b8d0738aab38fbc11f6a4831add0cba44f3bfdbe9295d

Observation dc4861cc-2d0f-4f2c-b0af-4dbecc5be481 · inbound

Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization cites this paper.

Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 16

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T14:01:07.052979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-09T23:42:00.548132Z digest=sha256:39ee57205475e36aa8ea14c2112a0d4d30ce811468e9092d9de128b5f667849c

Observation 76485794-02ab-44a8-b82b-a03c3f1dfa18 · inbound

From Skill Text to Skill Structure: The Scheduling-Structural-Logical Representation for Agent Skills cites this paper.

From Skill Text to Skill Structure: The Scheduling-Structural-Logical Representation for Agent Skills Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T00:14:26.953077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-08T04:05:49.308804Z digest=sha256:2a08d6651ed3e9951f0986d3665530fa7613d3e71f7dbd350b1447c0401fb17d

Observation 5477c902-6a50-4185-b039-aaaeb48e0cf0 · inbound

Heterogeneous Scientific Foundation Model Collaboration cites this paper.

Heterogeneous Scientific Foundation Model Collaboration Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 34

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T04:30:10.314670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-07T08:50:05.980191Z digest=sha256:1df4743bcd94947ab258e3ef56b0caf63b76a133439ec4e6f09b223c38ba4262

Observation 5d08643b-69a2-4aca-901a-b5ef14516330 · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 56

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T04:55:12.621864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-07T06:30:09.945371Z digest=sha256:1f10289ae382a57d2923cb4304b8c8df6fe2e2c307bdbb2bf0616640f9ac33a6

Observation ba2f0b0a-fc95-4bb0-919b-c0f7c136b14b · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 56

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T00:29:30.672325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-08T03:12:19.414358Z digest=sha256:518f2062f65505a6497730956784b15b1fb13626b52a2ed56e34bd8864ca431c

Observation 904ecb9e-9f0b-4894-b021-650a030c88f1 · inbound

Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.

Rethinking Agentic Reinforcement Learning In Large Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 56

Resolution
metadata mismatch
local_arxiv, observed 2026-05-19T17:02:40.450752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-19T16:58:41.558250Z digest=sha256:7417e4b888de7f286ce5d278def083b20343123a5e9b39e11e5975e8b74b7a49

Observation 52b10041-5f42-4b13-ad21-93accdcdf96b · inbound

DRIP-R: A Benchmark for Decision-Making and Reasoning Under Real-World Policy Ambiguity in the Retail Domain cites this paper.

DRIP-R: A Benchmark for Decision-Making and Reasoning Under Real-World Policy Ambiguity in the Retail Domain Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-05-11T02:40:55.668362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-11T02:40:27.234973Z digest=sha256:84a5bd1e8e8a23c5ce86eba116fbdef62f6a3fce7781bc5de5dc62fc50446085

Observation 8c2006b1-eba2-4aed-968b-6ca8aa5ffcca · inbound

Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values cites this paper.

Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-05-12T04:31:21.300308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T04:22:06.172150Z digest=sha256:96770f4790e8d9d6c94c5101740984cd8479e29340ad1368cea82e1747cec287

Observation 1ec2703a-19de-43ad-8904-46bbe13c991c · inbound

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning cites this paper.

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-05-12T07:06:33.627056Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-12T03:45:06.199636Z digest=sha256:d658afacd47dcafae6c5f236fd7329c33b2c2ef31414961605e000859c20df21

Observation c3ee15bc-86bd-4b4f-917a-7ee812196891 · inbound

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning cites this paper.

Dynamic Skill Lifecycle Management for Agentic Reinforcement Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-05-20T22:23:48.434440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-20T22:19:49.016156Z digest=sha256:23e9fd1323acb63a0336147e6bc1bde98abf35031f38806d8143a7816020df26

Observation 2361523b-ecd7-42c7-a7aa-dac6d962aa89 · inbound

Learning Agentic Policy from Action Guidance cites this paper.

Learning Agentic Policy from Action Guidance Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-13T05:07:17.594178Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-13T05:02:49.206053Z digest=sha256:5fcf8b0e3768d2579d3121e5c15413ac09f2f319d79a1bb373153bc942087afa

Observation 45a641c4-6fb3-4698-9c5f-65f2958bab27 · inbound

A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM$\Delta$ Integration into Upcycled MoE cites this paper.

A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM$\Delta$ Integration into Upcycled MoE Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-05-20T11:13:13.556985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-05-20T11:09:22.027588Z digest=sha256:93384226040e6de579749dd7b9489a02ac2b9a65023c1014ba8c06a6ca83e092

Observation f1e47612-d40b-4d9a-81ea-a6eee96055e3 · inbound

OEP: Poisoning Self-Evolving LLM Agents via Locally Correct but Non-Transferable Experiences cites this paper.

OEP: Poisoning Self-Evolving LLM Agents via Locally Correct but Non-Transferable Experiences Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-05-20T09:43:10.961509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-20T09:39:52.849575Z digest=sha256:638fd9125409fb597f47acc2ce5557cef1bb2e1b6bb2dc000adaf1970317ada4

Observation 758707e8-05c7-4f5a-8b56-31daaf3cf52c · inbound

Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs cites this paper.

Mix-Quant: Quantized Prefilling, Precise Decoding for Agentic LLMs Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-05-21T07:49:49.938591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-21T07:49:07.128814Z digest=sha256:e8c3fc733fba4828aa7397b96c347a0776b6dfc6537ca097a2bb34a3d6ca345f

Observation de91fe16-2418-472f-bcd0-2ed694e28a5e · inbound

From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills cites this paper.

From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-05-25T03:55:20.504052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-25T03:53:56.643075Z digest=sha256:88aead06baf79b89ba83e04bce6e3ae715ceab651b98bfdbb3b315eb6e5efcf0

Observation 436c4588-ac6e-401e-abd2-ff4632464fbb · inbound

Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems cites this paper.

Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 27

Resolution
verified exact
local_arxiv, observed 2026-06-29T21:13:59.495448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-29T21:13:03.346422Z digest=sha256:df26e887b99250031ecd45289ef90a14fd922173fa67fd0e4c0bcb33a3704ebf

Observation f6507533-0bb5-44a3-8d08-be438927743b · inbound

TrajAudit: Automated Failure Diagnosis for Agentic Coding Systems cites this paper.

TrajAudit: Automated Failure Diagnosis for Agentic Coding Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-06-29T16:13:35.847349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-29T16:13:30.977123Z digest=sha256:83c2e597d62659037b82a6b492bca523885cbbdd60e98738c8681edfebad3422

Observation 37a9641f-ea3d-4d61-9b0e-05e69f05931e · inbound

TrajAudit: Automated Failure Diagnosis for Agentic Coding Systems cites this paper.

TrajAudit: Automated Failure Diagnosis for Agentic Coding Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-02T13:09:16.811958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:09:16.811958Z digest=sha256:1218918d9d08560482de18b583e6dbc87de656c9846b3d6898ac318e57bce291

Observation f75984c9-70ab-4af9-b549-c547c2fbfaee · inbound

FundaPod: A Multi-Persona Agent Pod Platform with Knowledge Graph Memory for AI-Assisted Fundamental Investment Research cites this paper.

FundaPod: A Multi-Persona Agent Pod Platform with Knowledge Graph Memory for AI-Assisted Fundamental Investment Research Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-06-29T12:43:25.464143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-29T12:40:17.867815Z digest=sha256:37d2b529eff70c7ad3fabfc0dbb8c36b2b87708a83f7254b101250f5ee61dfb7

Observation 06b8671e-9118-456f-9e5a-67e7d587a0f6 · inbound

A Unified Framework for the Evaluation of LLM Agentic Capabilities cites this paper.

A Unified Framework for the Evaluation of LLM Agentic Capabilities Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-06-29T13:23:28.336244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-29T13:15:21.085584Z digest=sha256:11fdbf9010a5fed6aba8d699cb742578bdc57bda53ee7b81ef6761a1d8b841ee

Observation cde62cee-88fe-49e4-8b07-f5df62bf1cc8 · inbound

A Unified Framework for the Evaluation of LLM Agentic Capabilities cites this paper.

A Unified Framework for the Evaluation of LLM Agentic Capabilities Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T00:59:19.125776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-04T00:54:15.317631Z digest=sha256:4871105b51152e880840d0845f5b8146fe3d20da747f8e7ceaa464fe1c35d277

Observation 9db8b425-0973-4dc9-872e-03a782446201 · inbound

Skill or Skip? Learning Selective Skill Invocation in Agentic Tasks via Dual-Granularity Preference Learning cites this paper.

Skill or Skip? Learning Selective Skill Invocation in Agentic Tasks via Dual-Granularity Preference Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 59

Resolution
metadata mismatch
local_arxiv, observed 2026-06-28T19:12:34.086602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-28T19:10:18.320274Z digest=sha256:6787202c82457d11de7aed2e10598d23d1c7f435215d53d64025c8587a95a52e

Observation 25bbc1b5-5532-48b4-91a5-7adad21ea819 · inbound

Scaling Behavior of Single LLM-Driven Multi-Agent Systems cites this paper.

Scaling Behavior of Single LLM-Driven Multi-Agent Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 29

Resolution
metadata mismatch
local_arxiv, observed 2026-07-01T20:36:12.446399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-28T18:11:51.416335Z digest=sha256:90246ec539a28b501d7e5f9311c2791040d7037bad502855f09d5749fb953cd8

Observation 7e14e559-276d-41b1-b937-dd435a738158 · inbound

TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning cites this paper.

TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-07-01T21:26:16.513775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T16:53:24.776458Z digest=sha256:86df39a07f430e08e81c6cec92b1451b30d1245a1dbaf50d352427f32e96c00e

Observation 822a3328-2605-4d4d-9bc0-83ec011d66a9 · inbound

SeClaw: Spec-Driven Security Task Synthesis for Evaluating Autonomous Agents cites this paper.

SeClaw: Spec-Driven Security Task Synthesis for Evaluating Autonomous Agents Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-07-01T23:56:23.013656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T13:51:49.666484Z digest=sha256:339e82acd23122ead9eafe99315e71c897c13bb7afaae3339aa3459ecd8f0acb

Observation bfaa2eef-3061-48e3-84a9-e8d495339c07 · inbound

Beyond Alignment: Value Diversity as a Collective Property in Multicultural Agent Systems cites this paper.

Beyond Alignment: Value Diversity as a Collective Property in Multicultural Agent Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 38

Resolution
metadata mismatch
local_arxiv, observed 2026-06-28T02:01:28.978255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-28T01:56:56.127785Z digest=sha256:f5c40c6f3d5934f30e5b54206b4d8c0fc0f4f1b939b98349f706a0e33c7fdfa8

Observation 22c628e2-e825-4f30-b28f-a60f41c189ee · inbound

Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition cites this paper.

Workflow-to-Skill: Skill Creation via Routing-Workflow-Semantics-Attachments Decomposition Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-07-02T17:17:14.917720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T22:07:46.683185Z digest=sha256:8540f193081d4bedd897ecfc9bd595f2c8f33c121b94adf0ac3c21e86d04c8a0

Observation e3fc8623-f477-4180-aaaf-4e9542e1384b · inbound

Post-AGI Economies: Superposition and the Second Fundamental Theorem of Welfare Economics cites this paper.

Post-AGI Economies: Superposition and the Second Fundamental Theorem of Welfare Economics Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 46

Resolution
metadata mismatch
local_arxiv, observed 2026-07-02T22:27:25.640506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T18:56:37.173132Z digest=sha256:33c1d469f8bd4ef05ed41bd2551039c76ab1b8301a9165c6336b72a273b40f41

Observation 1271d399-03f5-4e68-8c11-2d8da966ab9d · inbound

A Robust Agentic Framework for Expert-Level Automation of Atomistic Simulations cites this paper.

A Robust Agentic Framework for Expert-Level Automation of Atomistic Simulations Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 22

Resolution
metadata mismatch
local_arxiv, observed 2026-07-03T02:57:35.129076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T15:40:03.181729Z digest=sha256:968086faa8f6831a946b70e1d8141e11a3eab31c16fa409bdb4eeac11caf5755

Observation 1d02a00c-0b11-4dc9-bfb1-7cc87fb8c11e · inbound

Civil Court Simulation with Large Language Models cites this paper.

Civil Court Simulation with Large Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-07-03T01:17:30.440231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T16:45:19.868954Z digest=sha256:09a6178af3428417150e5d5093976527fbb5e0865e52e3d114e3ad0082b443e9

Observation 97ef49c5-1581-4ff3-ae95-88bc3fa855fd · inbound

SkillJuror: Measuring How Agent Skill Organization Changes Runtime Behavior cites this paper.

SkillJuror: Measuring How Agent Skill Organization Changes Runtime Behavior Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-07-03T10:17:57.317585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T10:12:03.985549Z digest=sha256:9a515619bb98fa14a661832d7dcb7b15afd23a8946e65f1c802ad3191b490704

Observation dc4114ca-bde5-417f-b7dc-9b43469dcdce · inbound

LLM-as-an-Investigator: Evidence-First Reasoning for Robust Interactive Problem Diagnosis cites this paper.

LLM-as-an-Investigator: Evidence-First Reasoning for Robust Interactive Problem Diagnosis Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-07-03T14:38:29.245830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T06:58:42.823851Z digest=sha256:0f2983b29032cba2266a71fc4ad2ee3adfee8e3f265d3e324308cbaef38f378e

Observation 4d88e9a2-0be5-41a7-b888-4838860f9108 · inbound

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI cites this paper.

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 52

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no resolver link, observed 2026-08-02T11:29:21.972823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:29:21.972823Z digest=sha256:d5db8bf165c0e88c10de62974abdc509f281f364aa455231b451c29a10dd7308

Observation 14d13fc7-2e9b-413f-916c-b255d52a9689 · inbound

EnvRL: Learn from Environment Dynamics in Agentic Reinforcement Learning cites this paper.

EnvRL: Learn from Environment Dynamics in Agentic Reinforcement Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 21

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verified exact
local_arxiv, observed 2026-07-03T20:18:57.160536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T01:26:41.376368Z digest=sha256:95adeaff796f7af920dc5b322fdb41bc947d471bb151fe373f85d1c0c7aededb

Observation 6b9a6ab4-24cc-4519-b129-e74ad588b291 · inbound

RubricsTree: Scalable and Evolving Open-Ended Evaluation of Personal Health Agents across Health Memory and Medical Skills cites this paper.

RubricsTree: Scalable and Evolving Open-Ended Evaluation of Personal Health Agents across Health Memory and Medical Skills Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 22

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verified exact
local_arxiv, observed 2026-07-03T20:28:56.010914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T01:16:45.556397Z digest=sha256:20445b7086dc6a3861fdca95b6af0a67eb771f916264e67ba26f9a2cc8615479

Observation 307213c9-cea2-4c27-8a4e-c2739e89c693 · inbound

BioHarness: Substrate-Aware Evidence Assembly for Biomedical Question Answering across Literature, Knowledge Bases, and Biological Atlases cites this paper.

BioHarness: Substrate-Aware Evidence Assembly for Biomedical Question Answering across Literature, Knowledge Bases, and Biological Atlases Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 9

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verified exact
local_arxiv, observed 2026-07-04T03:09:28.894891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-26T18:34:09.474000Z digest=sha256:cf09e1fd7bedd43f9c743ddb17b83e1091af05afb81cae7f0bc830bb3b987add

Observation 88a461ad-777a-4212-ae0f-bb61e3221f11 · inbound

When Lower Privileges Suffice: Investigating Over-Privileged Tool Selection in LLM Agents cites this paper.

When Lower Privileges Suffice: Investigating Over-Privileged Tool Selection in LLM Agents Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

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verified exact
local_arxiv, observed 2026-07-04T04:59:35.658700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-26T16:35:03.492459Z digest=sha256:d02cfcd835a6407662d99c6505cb4f06ab7ef6a488326e2a5b40f11f7b8e28b4

Observation 7ecb11a5-7807-4747-947d-763f147421c2 · inbound

When Lower Privileges Suffice: Investigating Over-Privileged Tool Selection in LLM Agents cites this paper.

When Lower Privileges Suffice: Investigating Over-Privileged Tool Selection in LLM Agents Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

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unresolved
no resolver link, observed 2026-07-12T13:19:17.128158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T13:19:17.128158Z digest=sha256:57d1309fefb05a7a0054672d1197283eda066a26c440a173a5c81f2bf7537a83

Observation 1f56010a-5489-44f8-ab7b-b27909e03997 · inbound

From Question Answering to Task Completion: A Survey on Agent System and Harness Design cites this paper.

From Question Answering to Task Completion: A Survey on Agent System and Harness Design Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

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verified exact
local_arxiv, observed 2026-07-03T17:08:43.105689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-27T04:40:30.985824Z digest=sha256:6829c4bf6a5c38edccfa9f34960813ad3e5214d62dfebc500bc28b72ea1d5586

Observation cdbe696b-9235-4f54-b997-41b71f9cb873 · inbound

Group-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learning cites this paper.

Group-Graph Policy Optimization for Long-Horizon Agentic Reinforcement Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-07-04T10:29:45.772361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-26T08:44:23.085858Z digest=sha256:3af0d9d5056b56ed3064c5c60f71030002065b01c1061f7aca1798a49f23e040

Observation 05521bc2-7e2a-4c14-98fd-0033cd01cc27 · inbound

Managing Procedural Memory in LLM Agents: Control, Adaptation, and Evaluation cites this paper.

Managing Procedural Memory in LLM Agents: Control, Adaptation, and Evaluation Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 40

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metadata mismatch
local_arxiv, observed 2026-07-04T10:39:45.115627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-26T08:39:41.575494Z digest=sha256:d60f8684ac438b8c95202096c66038629108186d6ffbded9ff0c39c0a2513332

Observation c91552f8-8161-4b63-84be-7ae9424972de · inbound

TriggerBench: Investigating Prospective Memory for Large Language Models cites this paper.

TriggerBench: Investigating Prospective Memory for Large Language Models Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T10:39:46.210453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-26T08:33:56.650708Z digest=sha256:9b410aa9edf42ac6cbf3310a1c372bea3d0e9d6fc24ae6d25005a3c4c655078a

Observation d874211f-8af4-4c7d-adab-c1d978e811e4 · inbound

OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning cites this paper.

OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 13

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T13:29:51.600162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-26T05:07:16.926615Z digest=sha256:aab709dc693b278d1aaa1b45a9ba323408e4f476fd491c212681b3e36940cb4b

Observation bb21916c-aeab-4023-8723-163b81fd644c · inbound

RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources cites this paper.

RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 6

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verified exact
local_arxiv, observed 2026-06-30T02:24:13.801196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-30T02:14:27.968924Z digest=sha256:bd46aab4586f0cef542e0fe265086704982720b2459c1018bd3dbf3a760619d7

Observation 6d571ef1-39da-4f1c-abfc-5c81c8530d7d · inbound

RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources cites this paper.

RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 6

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no resolver link, observed 2026-07-15T10:24:06.533276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T10:24:06.533276Z digest=sha256:5f84c0af59a4d07b92cd832b118c3a4fc7a4457c0a398f2943b62ebc655b71ba

Observation cbd7b40b-da82-4a03-a64a-75dfe8ce8d62 · inbound

RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources cites this paper.

RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 2025

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no resolver link, observed 2026-08-02T09:43:49.231680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T09:43:49.231680Z digest=sha256:29da842efd2c535cc26e05fdb1de731c257911391a961dfacc9334d06f8bd11c

Observation 23f25462-db8d-4f12-b0b7-cf6140ff42cd · inbound

Mandol: An Agglomerative Agent Memory System for Long-Term Conversations cites this paper.

Mandol: An Agglomerative Agent Memory System for Long-Term Conversations Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-07-01T15:15:47.702954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-30T04:13:57.685952Z digest=sha256:6acd3eec39a633ee181ee6058abc81e0b05621c8ffd125a05c7af31da715532e

Observation 87322373-e774-45f1-b21d-c5d5e11ad5b6 · inbound

Measuring Harness-Induced Belief Divergence in Multi-Step LLM Agents cites this paper.

Measuring Harness-Induced Belief Divergence in Multi-Step LLM Agents Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 26

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no resolver link, observed 2026-07-11T17:54:49.531461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T17:54:49.531461Z digest=sha256:1d653e703f74cb71f92134e233783d3c710a9bc739c670e0d609c21973d7735a

Observation 9fd5422c-d669-4b1c-ae92-f134fdc2ea3a · inbound

TurnOPD: Making On-Policy Distillation Turn-Aware for Efficient Long-Horizon Agent Training cites this paper.

TurnOPD: Making On-Policy Distillation Turn-Aware for Efficient Long-Horizon Agent Training Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-07-09T00:35:48.708424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-09T00:29:35.583300Z digest=sha256:5edbed8e77d0a6d33c35145ad572d0e659c8b3be3ef642eb2bd48311789f796f

Observation 65457010-fe98-4169-afce-7a836ee30446 · inbound

LogicHunter: Testing LLM Agent Frameworks with an Agentic Oracle cites this paper.

LogicHunter: Testing LLM Agent Frameworks with an Agentic Oracle Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 31

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verified exact
local_arxiv, observed 2026-07-08T13:54:58.558500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-08T13:52:25.191385Z digest=sha256:253f1c5b2a3243145af4692e5ef2bd10619e8bf951e14b0c55a7a163f46d885a

Observation ab609727-3cc5-4d9c-9465-4d7f2fd201db · inbound

Artificial Persons cites this paper.

Artificial Persons Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T03:06:43.417801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-07-10T03:04:12.482618Z digest=sha256:e0b5f4c181b0c6cc970666af9c443581187dac36c40ca7aa4d878ef6a652e35b

Observation 1e1649db-2c60-431b-bd59-2458ae87ef77 · inbound

Artificial Persons cites this paper.

Artificial Persons Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

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unresolved
no resolver link, observed 2026-07-14T15:30:47.444899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T15:30:47.444899Z digest=sha256:8a46290ee9b1211419cc02d3c9f2f7cd0ec99dc3bd5815988f8e6deef190814f

Observation 93c4c438-ddcb-46ff-994b-0a57c0f7f787 · inbound

The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy cites this paper.

The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 160

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no resolver link, observed 2026-07-14T06:30:16.612345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T06:30:16.612345Z digest=sha256:ad2cb3f0667882e22f8583043233cb36342b1384aa939af2c5c0686aba323cb1

Observation d6ec817e-20b8-42b8-9629-c44f4c8a39ae · inbound

MyAG: A Graph-Based Framework for Designing and Analyzing Composable LLM Agent Systems cites this paper.

MyAG: A Graph-Based Framework for Designing and Analyzing Composable LLM Agent Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

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unresolved
no resolver link, observed 2026-08-02T05:07:09.087829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T05:07:09.087829Z digest=sha256:bc04556fea771ff9a5791b85df7a99777a193deebe248bdb4f0169c5f00dabe9

Observation 1f101cc2-10ee-45c8-96e3-02817646d475 · inbound

MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA cites this paper.

MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 31

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unresolved
no resolver link, observed 2026-08-02T01:48:36.613297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:48:36.613297Z digest=sha256:73e88b2f4ccf8bf65345e7cfb3bff60a1c82d5fe150dfd00fd05d33d93a190b9

Observation c847647a-97bd-4df9-9810-67857c7bc19b · inbound

Bad Memory: Evaluating Prompt Injection Risks from Memory in Agentic Systems cites this paper.

Bad Memory: Evaluating Prompt Injection Risks from Memory in Agentic Systems Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 15

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unresolved
no resolver link, observed 2026-08-02T01:38:40.521080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T01:38:40.521080Z digest=sha256:13e4ebb3c6d93893aa1ef82c0c76c9ca303502fa057e58b347e238c3305a872a

Observation ae2fdea5-7636-4866-84c8-4c760c4c676c · inbound

SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning cites this paper.

SEED: Self-Evolving On-Policy Distillation for Agentic Reinforcement Learning Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-02T01:10:21.233653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T01:10:21.233653Z digest=sha256:42c46ec4118d3349b438d76c29b946af176cf7c3f0fd739815255abc7e2a5325

Observation 7a06a227-e7cd-433c-8266-dd376676b65a · inbound

OpenSkillRisk: Benchmarking Agent Safety When Using Real-World Risky Third-Party Skills cites this paper.

OpenSkillRisk: Benchmarking Agent Safety When Using Real-World Risky Third-Party Skills Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 3

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unresolved
no resolver link, observed 2026-08-01T10:46:12.122548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T10:46:12.122548Z digest=sha256:e9bcc7ed7fcafc12be728e76c44236e81132a78ec2e009023810b081b4155767

Observation 0d96277a-ba51-47e0-bf7f-0e447c7844a8 · inbound

CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering cites this paper.

CAGE: Cognitive Attribution Graphs for Faithful Inline Citation Generation in Long-Form Question Answering Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 28

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unresolved
no resolver link, observed 2026-07-31T20:22:23.646994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T20:22:23.646994Z digest=sha256:010ebc07c03e24ad599a66216504a6dde5cc20843d6cfe1d339254fd39872f04

Observation 84225915-e208-45d9-a76a-ac6195a91860 · inbound

Multi-Agent Debate Strategies: Survey, Taxonomy, and Challenges cites this paper.

Multi-Agent Debate Strategies: Survey, Taxonomy, and Challenges Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 78

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no resolver link, observed 2026-08-01T00:32:30.485982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:32:30.485982Z digest=sha256:beb46fd3370727f50c0367a9d29bb1a6363d3d5c1002d25d2bc4981f6250bbe7

Observation d3867f54-df4e-46c7-9b88-2c2e4e5ba7da · inbound

Autonomous Repair for Multi-Agent Systems via Monte-Carlo Tree Search cites this paper.

Autonomous Repair for Multi-Agent Systems via Monte-Carlo Tree Search Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 34

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unresolved
no resolver link, observed 2026-08-03T14:33:33.690998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T14:33:33.690998Z digest=sha256:a80cbb37596feb2013a29efa0d5cd1273fbdf86bd6cb6cb8ebdf11d7131f3129

Observation 1d19e065-62f4-4212-8cd4-d2797c9c97d1 · inbound

Rethinking AI Cloud Infrastructure for Agentic Serving Systems with the Aries Experimentation Framework cites this paper.

Rethinking AI Cloud Infrastructure for Agentic Serving Systems with the Aries Experimentation Framework Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Reference 27

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no resolver link, observed 2026-08-03T14:14:11.467611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:14:11.467611Z digest=sha256:77cb0e6369b0553d45c5565b4e5fbc52fe47b0391579dc6ac0b2720f2f7d0172