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Paper Citation Record · LEDGER

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As of 8 August 2026, this Paper Citation Record lists 97 of 97 outbound references and 8 inbound Pith citation observations for arXiv:2505.17716.

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

pith.paper-citation-record.v1
2505.17716 v1

Coverage vector

measured 97 of 97 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:44:31.351435Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:34:58.922731Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:58:57.420819Z

Reference resolution

97 of 97 outbound references displayed

  • verified exact5
  • verified fuzzy0
  • unresolved91
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 41e24c31-b48e-45b1-a0c3-278b44f01992 · outbound

This paper cites Workflow Use.

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Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.623706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.623706Z digest=sha256:4047b8e1bdcea298ed9d581660df97dc69bc43524ab7c605861c5e48638ccad4

Observation 92430e5d-8a27-48fe-abc1-fc56bd17bfc3 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.716221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.716221Z digest=sha256:dd50b9188b666a70153a545187fbbd4e1ca2297fce679d5aaef2670529a229a6

Observation cfed8277-e996-4e49-96fb-f262de392385 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.820445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.820445Z digest=sha256:380769c5cec1733f9eaae6d33b6c18439002a6c1222a7fe3d6cbc4ae2cceae07

Observation bc0d75a4-8308-4dae-9f35-f895117136e7 · outbound

This paper cites AirGapAgent: Protecting Privacy-Conscious Conversational Agents.

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Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:21.931565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:21.931565Z digest=sha256:349c8af954403fe07f640a65a8555d61bfb536291598e54b3a7cd0e4122e7529

Observation 37cc5a43-6b71-4efe-8d4f-bb11ff46f010 · outbound

This paper cites LLMs Will Always Hallucinate, and We Need to Live With This.

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Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.019183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.019183Z digest=sha256:eb8283b4c847a92f1af76b649262423cd10d813dc8c1bc5c4ca4ed0b1c6d1c9f

Observation 537e038e-01fe-445b-a2dc-992b621933fa · outbound

This paper cites SagaLLM: Context Management, Validation, and Transaction Guarantees for Multi-Agent LLM Planning.

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Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.092192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.092192Z digest=sha256:852fc4a4f7eebec76845ceb3fffba7015a5c676900e178adff886b243a50ccc7

Observation 630895a8-50c6-4bbc-b73f-3489133076ea · outbound

This paper cites Fine-Tuning Large Language Models with User-Level Differential Privacy.

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Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.165394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.165394Z digest=sha256:7adf1037cda9611813d0e1d14cead1a1d192c3a8b1bae3acdf624a6ae9cf4ad0

Observation 150a8806-5a0c-47bd-bad3-3e2fe54f5d5d · outbound

This paper cites The Obvious Invisible Threat: LLM-Powered GUI Agents' Vulnerability to Fine-Print Injections.

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Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.237391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.237391Z digest=sha256:a77ff93757e80367442a1b30ac5d5d388286f2abc0353fe75e3da42f0fa29f08

Observation 66a16f67-897b-4287-ab90-c37253fd370d · outbound

This paper cites CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applications.

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Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.342841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.342841Z digest=sha256:51a3a662ebbd72db5871030f4cd1da1a1737db339904f584b60ee016978a3e29

Observation 4d8aec58-7fdd-49aa-be59-a69587955790 · outbound

This paper cites ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning.

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Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.442472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.442472Z digest=sha256:47694941f231e0f3bae8fa7ddaf93d1575c41a90334f3a8401b4114f95808305

Observation 915c38dc-f076-4c53-95d6-34ba436c3669 · outbound

This paper cites Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory.

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Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.533849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.533849Z digest=sha256:e0ac5c0d1d7e6a3dd30110d5cd41fa41883816b0bda18d0c7c425dfd6850132d

Observation b0f46c86-94f2-4f03-aeb7-17cae6fcdc37 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.610417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.610417Z digest=sha256:692335daf6897829ba3fd98026070a2c67136fa617374a34aa74aaeee1ff66d2

Observation a0a4f8b2-b913-4353-b3f2-940c93926836 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.701647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.701647Z digest=sha256:af92377c82430fcf93d93988e59e944bd1c4c5575e5d6e806bb3052eb56a13b7

Observation af0f196e-a1bc-4f49-ab37-ddb967b841a0 · outbound

This paper cites Open Challenges in Multi-Agent Security: Towards Secure Systems of Interacting AI Agents.

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Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:22.864946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:22.864946Z digest=sha256:57715f3ea9c2174d87e6261a216e7a7511c6d965b648266d6f754f9ff29e6207

Observation dd70692f-3659-4cc7-b7ed-77ea7467f4f4 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.015401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.015401Z digest=sha256:ab7452957060eb15552956e40c0a444b755449c0301cbd12ba8754fbb256385f

Observation 0d10b42b-515c-40a5-b47a-0fafba6430f3 · outbound

This paper cites Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster.

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Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.116345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.116345Z digest=sha256:d297c30c63705e88755d5474430df8659c786ac664af1c824afd44ee0100b51a

Observation 7b6c9bad-d0d5-4c83-be8e-559423637ada · outbound

This paper cites Building Guardrails for Large Language Models.

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Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.169749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.169749Z digest=sha256:27f1bf4a899308b04e5328f9f380c338382ef63c3c58d3dcb2006c9de9ce5c21

Observation aac9bb44-f36d-488a-8da0-8cff6d5dd7b3 · outbound

This paper cites MxMoE: Mixed-precision Quantization for MoE with Accuracy and Performance Co-Design.

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Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.206783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.206783Z digest=sha256:1328648edab30d33a6d7bf76473c956b3e2af12186acc2ee9eecea2d5a70ba99

Observation d5453964-4ae2-4241-9deb-9ad9132be92a · outbound

This paper cites ReTool: Reinforcement Learning for Strategic Tool Use in LLMs.

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Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.211372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.211372Z digest=sha256:4c6c717212f23e3869dfc539f0ea884c9aecb803df2ada26d4295c13b56bd9a7

Observation 221c8c36-5f1a-46d6-b59c-745ce941af8e · outbound

This paper cites Towards Efficient Record and Replay: A Case Study in WeChat.

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Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:44:34.145798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:44:23.216049Z digest=sha256:b4226cdc9a23fa453b11ed3c5193df373fb2109b2ed9ba44291d436c8ecce834

Observation 7d9a689a-d348-4f41-ba2b-8d9e55855340 · outbound

This paper cites I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders.

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Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.234479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.234479Z digest=sha256:ad3392bfa5cd76646b312c869ae4379d3b16716f00aa7d2676f771b947009685

Observation 15bb2341-a93d-415d-9512-251a6bfc6e8e · outbound

This paper cites Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey.

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Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.275355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.275355Z digest=sha256:ce91c6a71ad0ca4a970d8e53f72bea38e6688f03d3e0f5d764cf1a255a764654

Observation a6c0d282-3272-4465-ae5b-ae389312df35 · outbound

This paper cites A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models.

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Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.313148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.313148Z digest=sha256:09671a23da3c1b3d2517b4d5ba75a95e2f4c7260d45e51f20ee5524846f197b6

Observation 71362ded-996a-4e10-8c80-66dfb4b9f1e6 · outbound

This paper cites Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use.

Get Experience from Practice: LLM Agents with Record & Replay Synthetic Data Generation & Multi-Step RL for Reasoning & Tool Use

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.355764Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.355764Z digest=sha256:2e7e73959779745cc332b0c1ccea5a38cc08bdd7803cee8cf216432fa9e118bc

Observation 5dc8f669-2a0f-4665-bcb2-bdb81f2ed371 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.431178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.431178Z digest=sha256:93fa4f91d2ef9f7135c4c5d186b9da938002871f0721ba8abfed7915f28dc2dd

Observation e167ea5a-9c88-4604-b656-1a484180d665 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.514961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.514961Z digest=sha256:339706523db956609a6de6de438b6f7c6a650ae1a58015fab81cf1ffd718a747

Observation 358b56e5-8dae-4abc-aa35-e0cbf2f7b780 · outbound

This paper cites MiniLLM: On-Policy Distillation of Large Language Models.

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Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.608742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.608742Z digest=sha256:6a46a01d905e84879a3399e3494d016d1c32d2fc730e005e10707202988819f3

Observation 17075482-ebc7-4d9a-8339-7625d35d6f50 · outbound

This paper cites Building A Secure Agentic AI Application Leveraging A2A Protocol.

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Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.743076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.743076Z digest=sha256:198f297498bbe30cc0463e53f4882f86a905ef7152ec4a0ad648d72063ccb72a

Observation 3a0cb11b-a5c1-4def-8d58-2e337b8d1272 · outbound

This paper cites Bridging the Safety Gap: A Guardrail Pipeline for Trustworthy LLM Inferences.

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Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.855111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.855111Z digest=sha256:425444f81e6428f61ae11653f8d9d8333e6c42422fb6e709d525ed93e8004f49

Observation 5c6e9611-ed64-4256-9730-dffd85d5381e · outbound

This paper cites Instruction-Following Pruning for Large Language Models.

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Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:23.951879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:23.951879Z digest=sha256:afa32a841c7988132cf73f763ee58c8c7541fe9773e6261de560c41fad5e9e5a

Observation 8a210463-3589-4c08-86ec-15b7e6b12de1 · outbound

This paper cites Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions.

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Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.064474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.064474Z digest=sha256:44b7487a2b83b9e35f2704e02a81282399dbe43d0a11bdb449a382c935eec9a3

Observation eaf7abcf-b213-444e-ba90-3a13148a4ce0 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay LoRA: Low-Rank Adaptation of Large Language Models

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.144513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.144513Z digest=sha256:c868058a679e754c5724663b7d15ddf139e0308fa4d3b71b0c2104f1f494a4f9

Observation 014c392e-13c8-4eab-9ee7-206eeae34f76 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.254468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.254468Z digest=sha256:c80b27ac337a1b8de070d36a2ede68308596903d1a959a891493bccb56243211

Observation 9d92ee5a-d4ce-4cc8-a074-cf5e180bf1fd · outbound

This paper cites R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory.

Get Experience from Practice: LLM Agents with Record & Replay R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.367410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.367410Z digest=sha256:f4bd72fab58ccb2ff008b80588ff4e1bacd64fdd896df8571c1f9c3149a110f7

Observation 14482955-bc17-4358-9bad-7c5ecaf83bed · outbound

This paper cites $R^2$-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning.

Get Experience from Practice: LLM Agents with Record & Replay $R^2$-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.482001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.482001Z digest=sha256:8f867925cf4e24bbc6c64201092c0de327b4f7a8b41647e5847283d6c9b0ec9c

Observation 5f4a6291-f63f-4143-b89b-bbc4ec90e402 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.563126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.563126Z digest=sha256:775158f08cf6b023fe2c0b2e17036c0113a2377c6c79147ab6c7e836c6800c4a

Observation b30c4fe7-afb1-4d22-82df-1120b9428702 · outbound

This paper cites When LLMs Go Online: The Emerging Threat of Web-Enabled LLMs.

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Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.672026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:24.672026Z digest=sha256:b649cb25e08d9670fba4b53f395e3b634178662954396b40ac898919b1bf8f41

Observation d5a9528f-ad38-4fe6-8863-8c0d42c8ee3a · outbound

This paper cites LoRA-Switch: Boosting the Efficiency of Dynamic LLM Adapters via System-Algorithm Co-design.

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Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:44:24.752407Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:44:24.752407Z digest=sha256:359dbafe880b71764180471b6acc38155024bea303486e7e80038a1da103b051

Observation eb9bb32d-f13b-4a16-9207-cc8a9472e4db · outbound

This paper cites RT-Cache: Training-Free Retrieval for Real-Time Manipulation.

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Reference 39

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source=pdf_text observed=2026-08-07T14:44:24.896006Z digest=sha256:1d57ef4a5adb8313afc4d18a8b3d5af4a50bcb4936f92c2acdbc2ed441622091

Observation d749a6c7-5ef3-4ab9-ac50-8e7498fd0572 · outbound

This paper cites an unresolved cited work.

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Reference 40

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source=pdf_text observed=2026-08-07T14:44:25.024385Z digest=sha256:203def0f6dea44f68b85da35374d0fd1c0f57cc4b0ed747e7ba2dbc5d0277bbd

Observation ee62f678-68e6-41f9-9d17-d5186a03d75d · outbound

This paper cites TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models.

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Reference 41

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source=pdf_text observed=2026-08-07T14:44:25.216265Z digest=sha256:0b00442714fedd69889420f15dfc971bec4be71f52f0aad0b83cac498349d2bb

Observation cd5a48d4-84d6-4b8e-bd54-1cf25659c5cf · outbound

This paper cites ACE: A Security Architecture for LLM-Integrated App Systems.

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Reference 42

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source=pdf_text observed=2026-08-07T14:44:25.389219Z digest=sha256:afc007dd24d5f4d887fb17a1702bc71fd8b77b32920ce541f2f936ab4605da02

Observation a02fb9e6-cee7-453c-8c60-da1e8f7e2227 · outbound

This paper cites Enhancing Retrieval-Augmented Generation: A Study of Best Practices.

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Reference 43

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source=pdf_text observed=2026-08-07T14:44:25.538757Z digest=sha256:4945c49ccbe36592b90605c28e5182456b035bf4393cf457974b7a746051945a

Observation 57fa5b82-10af-4c2f-b971-88517283d9f4 · outbound

This paper cites Large Language Models Can Be Strong Differentially Private Learners.

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Reference 44

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source=pdf_text observed=2026-08-07T14:44:25.655123Z digest=sha256:6d60f6bd4a5aad97a5e801257a94c0c190f336835126660aaa5d254da7e9fc62

Observation 32e9b4c8-21d2-40d7-8ce9-9937ff5f51b5 · outbound

This paper cites Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models.

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Reference 45

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source=pdf_text observed=2026-08-07T14:44:25.766462Z digest=sha256:ebf42a28aea0a1562741aea43c7c051d4fac086544eaa3afb1d97a4db684bcb3

Observation 7af17398-9292-4b95-bbac-022fd8ff71d5 · outbound

This paper cites Gonzalez.

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Reference 46

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source=pdf_text observed=2026-08-07T14:44:25.908238Z digest=sha256:9b8f9357ba6b873e88456a745e52e9f3e6a683b88c3f1f812415ab16a01739ff

Observation d61d0b48-e320-44d0-bb49-18904d608e4d · outbound

This paper cites SlimGPT: Layer-wise Structured Pruning for Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay SlimGPT: Layer-wise Structured Pruning for Large Language Models

Reference 47

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source=pdf_text observed=2026-08-07T14:44:26.235980Z digest=sha256:e9f71db03526de19ccd4cd777612fb960ef45decaafc87dfc5b5a911cc3e400e

Observation ee0dd90a-7894-499a-bf0b-e341fb3c6c2b · outbound

This paper cites Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems.

Get Experience from Practice: LLM Agents with Record & Replay Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems

Reference 48

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source=pdf_text observed=2026-08-07T14:44:26.359633Z digest=sha256:8cfa247e1d310419c62fb22393b9a7f94695c0c60de5beb456b78fa49a3ea98f

Observation d503717f-c057-4032-bd8e-ebc1324605e7 · outbound

This paper cites Efficient Inference for Large Reasoning Models: A Survey.

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Reference 49

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source=pdf_text observed=2026-08-07T14:44:26.481418Z digest=sha256:345993fc7434afb61eba82950bbc0989fa69f8bbf5fbac87cfc0667e1b4db733

Observation 8185b8d3-6295-4e2e-a530-3c59cd2927fc · outbound

This paper cites Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation.

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Reference 50

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source=pdf_text observed=2026-08-07T14:44:26.633779Z digest=sha256:d35a9cf95ee2e7d77bc71a2ca74e15b471c66aa29fa5c7581168099fb0112eab

Observation 69a2e8ab-2c88-4722-bcb5-184158884a42 · outbound

This paper cites an unresolved cited work.

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Reference 51

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source=pdf_text observed=2026-08-07T14:44:26.731160Z digest=sha256:14dae07629f31de410bbfe0b6b7bdc2b2af7ed986f524a6b53325bcc58cb7bbf

Observation 3bb98f6c-2b2b-467c-8b5e-149a61a3faaa · outbound

This paper cites an unresolved cited work.

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Reference 52

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source=pdf_text observed=2026-08-07T14:44:26.812812Z digest=sha256:434b48dc137eb8dc346e3d77726ba23035a91b51b2a20b5d4fb6482715e5dd28

Observation cb746375-f049-414c-a6ef-9e4f50a47f6e · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 53

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no resolver link, observed 2026-08-07T14:44:26.949225Z

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source=pdf_text observed=2026-08-07T14:44:26.949225Z digest=sha256:44e4bbce2f7ca0cff3381e48c911439923830a4901c5beed1606e385571964c6

Observation 19867453-7e49-45c5-aec6-44965de8af43 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 54

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no resolver link, observed 2026-08-07T14:44:27.021816Z

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source=pdf_text observed=2026-08-07T14:44:27.021816Z digest=sha256:f7e09b3253773db453e07065364a4b615610ea4befd35b8b01c8e7fdf124ff33

Observation a27b0095-2a01-4d51-8026-2f05909fef83 · outbound

This paper cites Federated Intelligence: When Large AI Models Meet Federated Fine-Tuning and Collaborative Reasoning at the Network Edge.

Get Experience from Practice: LLM Agents with Record & Replay Federated Intelligence: When Large AI Models Meet Federated Fine-Tuning and Collaborative Reasoning at the Network Edge

Reference 55

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verified exact
local_arxiv, observed 2026-08-07T14:44:33.405295Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:44:27.142810Z digest=sha256:dd35b597c32ed3216f4762568f177faaef00686c2f9c45d37006d96b08f2184e

Observation a2287149-61c6-491e-ab33-e5795d603465 · outbound

This paper cites an unresolved cited work.

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Reference 56

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source=pdf_text observed=2026-08-07T14:44:27.266489Z digest=sha256:15257f836ad9b2dcf879a0ac55828e8249a6254953098522358e4443797ee50a

Observation a6d3e755-bd33-4607-bc77-743f0360855b · outbound

This paper cites an unresolved cited work.

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Reference 57

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source=pdf_text observed=2026-08-07T14:44:27.345119Z digest=sha256:2dd4ba3d30b1464ba9af004770406b2a6263f3c87b49dd9fb3fb51f4579de657

Observation 7077b278-696b-44e5-9fc9-c73e823b450f · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 58

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source=pdf_text observed=2026-08-07T14:44:27.613927Z digest=sha256:37e5fc2f2ecafeb32df19738731fb3b60a6e82e22bafbe2ec91bb694e6c5f6d7

Observation b92a7833-ad6c-4f4b-bebc-25588f06499c · outbound

This paper cites A Generalist Agent.

Get Experience from Practice: LLM Agents with Record & Replay A Generalist Agent

Reference 59

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no resolver link, observed 2026-08-07T14:44:27.822343Z

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source=pdf_text observed=2026-08-07T14:44:27.822343Z digest=sha256:8d8dc26f3bf16a629b6af3f7c7c20097c6477c551d6193a36555cc58aeb740a5

Observation 7699b73d-2bcb-4537-9c75-d39a5ff35452 · outbound

This paper cites DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition.

Get Experience from Practice: LLM Agents with Record & Replay DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition

Reference 60

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source=pdf_text observed=2026-08-07T14:44:27.916339Z digest=sha256:bee6ccebc904e393c0f080b88213a3e758cb0a8a51f0f686ef4487d0e79e3d3f

Observation b7b8a427-da5c-4053-aed3-177df5d14bde · outbound

This paper cites A Proposal for Evaluating the Operational Risk for ChatBots based on Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay A Proposal for Evaluating the Operational Risk for ChatBots based on Large Language Models

Reference 61

Resolution
metadata mismatch
local_arxiv, observed 2026-08-07T14:44:33.053411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:44:27.742266Z digest=sha256:efd2df6789223e757b72f5f82bc28aafad2fb7988c62881a5781fd88e8da6098

Observation 7ddc65b9-8ded-43f0-a0c5-7d6ccfe7e8bb · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 62

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source=pdf_text observed=2026-08-07T14:44:28.138446Z digest=sha256:76a27c1d798911e08013e391d96cda23226ef9ff416c8472df2993f90c9d871b

Observation 960fdf45-8f3d-4f63-a8de-113ea7627036 · outbound

This paper cites Lee, and Josep Torrellas.

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Reference 63

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source=pdf_text observed=2026-08-07T14:44:28.228407Z digest=sha256:99ffef9396b4d2444f7e69d561b6e23c65d94c7676be414a0334ea344482a425

Observation 39645ccb-d26c-41c5-80ff-275f6bb40070 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 64

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no resolver link, observed 2026-08-07T14:44:28.023920Z

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source=pdf_text observed=2026-08-07T14:44:28.023920Z digest=sha256:854fe086e4f13da646b1ae262d3a8cea8708cab96bb591791b2898661cb7a499

Observation b105c3a5-fa8c-40c6-9513-43e0b16022aa · outbound

This paper cites From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent.

Get Experience from Practice: LLM Agents with Record & Replay From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent

Reference 65

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no resolver link, observed 2026-08-07T14:44:28.393229Z

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source=pdf_text observed=2026-08-07T14:44:28.393229Z digest=sha256:f2113585b19460aa925ba518d4f99010851fb9994b68d6339d2d8b212ca8a6f9

Observation 3f641d6f-72a4-47da-8750-99b4926d36ed · outbound

This paper cites S-LoRA: Serving Thousands of Concurrent LoRA Adapters.

Get Experience from Practice: LLM Agents with Record & Replay S-LoRA: Serving Thousands of Concurrent LoRA Adapters

Reference 66

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source=pdf_text observed=2026-08-07T14:44:28.529284Z digest=sha256:dd684c2d5c4f75913bc36b86370c6416d573c2d6eacb6f12a5f65792a1ab18b7

Observation fda44509-cab7-43b2-9103-5c371ad06f07 · outbound

This paper cites Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents.

Get Experience from Practice: LLM Agents with Record & Replay Division-of-Thoughts: Harnessing Hybrid Language Model Synergy for Efficient On-Device Agents

Reference 67

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source=pdf_text observed=2026-08-07T14:44:28.320095Z digest=sha256:0e3a8d9006d873b0e05a742bade9bd1a65a92850060b1bcf6df5d5df0dc99738

Observation c51d5d75-343e-4cb9-a882-1fa4053f1ed3 · outbound

This paper cites Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG.

Get Experience from Practice: LLM Agents with Record & Replay Agentic Retrieval-Augmented Generation: A Survey on Agentic RAG

Reference 68

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no resolver link, observed 2026-08-07T14:44:28.742813Z

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source=pdf_text observed=2026-08-07T14:44:28.742813Z digest=sha256:f9d2129f2a7067eb6a91c9119eb4b2150a75ecbfd22ea8c094404a89de028125

Observation 60bbecd0-3665-4f43-bff7-cf65d971ceb2 · outbound

This paper cites Can You Mimic Me? Exploring the Use of Android Record & Replay Tools in Debugging.

Get Experience from Practice: LLM Agents with Record & Replay Can You Mimic Me? Exploring the Use of Android Record & Replay Tools in Debugging

Reference 69

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:44:32.468956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:44:28.832097Z digest=sha256:58c8b9e52a1011e130e6e4ff27316cd2fa9aedeb54270f9182707d888533ead2

Observation 581bd1e3-da7a-4c84-a7c3-be256775e294 · outbound

This paper cites FlowAgent: Achieving Compliance and Flexibility for Workflow Agents.

Get Experience from Practice: LLM Agents with Record & Replay FlowAgent: Achieving Compliance and Flexibility for Workflow Agents

Reference 70

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no resolver link, observed 2026-08-07T14:44:28.651341Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:44:28.651341Z digest=sha256:4c1f1eab9ac4f8ede661ef56f74f362a2aa893567c0bd1bd600a20e6f127b6f8

Observation 6987f857-a898-4891-89bd-816eeb27d00a · outbound

This paper cites A Simple and Effective Pruning Approach for Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay A Simple and Effective Pruning Approach for Large Language Models

Reference 71

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no resolver link, observed 2026-08-07T14:44:29.040161Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.040161Z digest=sha256:a4e748f903d783f759d38306dd72c49648d74bdf167fcef936ce664a02773009

Observation b91abf6b-71c7-4e8d-bcc3-4c82e5b5459f · outbound

This paper cites Fast-Slow-Thinking: Complex Task Solving with Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Fast-Slow-Thinking: Complex Task Solving with Large Language Models

Reference 72

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source=pdf_text observed=2026-08-07T14:44:29.166622Z digest=sha256:d5880053c2d4bbe182fddaed806794c985164d1b2e1d1f6da89b29daeeb016a7

Observation b93cff18-f9c7-4b29-976f-43f12e3e446a · outbound

This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models

Reference 73

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source=pdf_text observed=2026-08-07T14:44:28.962167Z digest=sha256:4a1362266a3bd01cb4db512852a15564cf7714929ba92f187a7e31311bfd93b1

Observation b448936a-2d07-4665-949a-6e70ebc30046 · outbound

This paper cites Gemma 3 Technical Report.

Get Experience from Practice: LLM Agents with Record & Replay Gemma 3 Technical Report

Reference 74

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no resolver link, observed 2026-08-07T14:44:29.458371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.458371Z digest=sha256:cf0b161e514f7ad93bb42dd943a6fa8b6b77230e501d53d427e46c7164f7d460

Observation 49c4bff2-63cc-4cb6-90c8-0991111fcfef · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 75

Resolution
verified exact
doi, observed 2026-08-07T14:44:31.545999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:44:29.585105Z digest=sha256:ce66620d1163184dcbdb981c00975ccaf5d01142cdbe98e207cf6fab6e2c3487

Observation 5a1c83ae-065e-4477-b412-4df8d725b46b · outbound

This paper cites Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Equilibrate RLHF: Towards Balancing Helpfulness-Safety Trade-off in Large Language Models

Reference 76

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unresolved
no resolver link, observed 2026-08-07T14:44:29.293072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.293072Z digest=sha256:f0941ab795f43a8dc7468e175fdfb995d220407c44bd585a6b9c507a7b248a9d

Observation 8a4eb285-b48c-484c-acb6-a60cdd51e0b2 · outbound

This paper cites A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment.

Get Experience from Practice: LLM Agents with Record & Replay A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 77

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no resolver link, observed 2026-08-07T14:44:29.819479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:44:29.819479Z digest=sha256:22b5dc8194a18ce7518ccf66ead98cd675125026ae64f4938feb3df69bd71e4e

Observation 26c69b02-4de2-4ea3-a0f2-f3937dc3a5f9 · outbound

This paper cites Tina: Tiny Reasoning Models via LoRA.

Get Experience from Practice: LLM Agents with Record & Replay Tina: Tiny Reasoning Models via LoRA

Reference 78

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source=pdf_text observed=2026-08-07T14:44:29.928994Z digest=sha256:91a9370d6524faafa4a9b06f37a0b10d6e472f3ffa5758a1de2c397578592298

Observation 5678a4a2-2ee3-49dd-8166-22031c443bac · outbound

This paper cites BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs.

Get Experience from Practice: LLM Agents with Record & Replay BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs

Reference 79

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source=pdf_text observed=2026-08-07T14:44:29.723829Z digest=sha256:2c73a484ff079ca051dbe5996b2209941c87c20e129558b444c692206101a77e

Observation e44114ca-c3bd-48af-953b-2609496cef07 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 80

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no resolver link, observed 2026-08-07T14:44:30.159597Z

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source=pdf_text observed=2026-08-07T14:44:30.159597Z digest=sha256:58b0a07a313fccd8cbac24e52b1d19e6b8020427516f1fa6ca46d44402dbea03

Observation 596e1474-6c0f-410e-b7ad-6b0edabae4fb · outbound

This paper cites Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks.

Get Experience from Practice: LLM Agents with Record & Replay Mobile-Agent-E: Self-Evolving Mobile Assistant for Complex Tasks

Reference 81

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no resolver link, observed 2026-08-07T14:44:30.416444Z

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source=pdf_text observed=2026-08-07T14:44:30.416444Z digest=sha256:114aa77db083a8930602465e96b74508c9f06960b36da1dcaac07a0b6fae28ab

Observation ef7ffe5d-29ee-4cb9-a457-ac9f10257f54 · outbound

This paper cites DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay DART-LLM: Dependency-Aware Multi-Robot Task Decomposition and Execution using Large Language Models

Reference 82

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source=pdf_text observed=2026-08-07T14:44:30.075020Z digest=sha256:242bf49c982619e741f7c2a75b00c37c571907bef70bb27196c44facfdd43c15

Observation d6027c28-87f7-4c77-9cfe-c85e608cc3a0 · outbound

This paper cites Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy.

Get Experience from Practice: LLM Agents with Record & Replay Cape: Context-Aware Prompt Perturbation Mechanism with Differential Privacy

Reference 83

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verified exact
local_arxiv, observed 2026-08-07T14:44:32.033083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T14:44:30.556770Z digest=sha256:326da3cea10ddb57b6b6c7e294dfd80a08143f3e11dcaaff2d08653cbf135761

Observation 8cbd9611-d375-4820-bb82-4c423f530f30 · outbound

This paper cites Reinforcement Learning for Reasoning in Large Language Models with One Training Example.

Get Experience from Practice: LLM Agents with Record & Replay Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Reference 84

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source=pdf_text observed=2026-08-07T14:44:30.331311Z digest=sha256:a2abd7a889510438e4e773bd795e0f122938476af6c97663f6c985d512f3bfa9

Observation e04c5f9c-03e2-470a-bf13-004b482d53c5 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

Get Experience from Practice: LLM Agents with Record & Replay ReAct: Synergizing Reasoning and Acting in Language Models

Reference 85

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source=pdf_text observed=2026-08-07T14:44:30.678374Z digest=sha256:eb233515cb859d5c5bddb68151f1762be41b51249120937ec27d4933a51b6ded

Observation ea4ef6c8-cf92-4d34-bb53-3365c52bbbdf · outbound

This paper cites Base Models Beat Aligned Models at Randomness and Creativity.

Get Experience from Practice: LLM Agents with Record & Replay Base Models Beat Aligned Models at Randomness and Creativity

Reference 86

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no resolver link, observed 2026-08-07T14:44:30.481737Z

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source=pdf_text observed=2026-08-07T14:44:30.481737Z digest=sha256:571248ecdafb2f779cd3e111c9d3ecb27b7cc4abdcd9e2da8805f75e31c0ee5a

Observation 4bb40898-03fb-41e3-b4b3-2d111ac82ee2 · outbound

This paper cites an unresolved cited work.

Get Experience from Practice: LLM Agents with Record & Replay Unresolved cited work

Reference 87

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no resolver link, observed 2026-08-07T14:44:30.849701Z

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source=pdf_text observed=2026-08-07T14:44:30.849701Z digest=sha256:4489036e451073e606b687f01c62feda3b00d61b9bc2777dee4ad15fee1ed8c6

Observation ad5221f1-1714-46ad-8076-f4583c2a30da · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

Get Experience from Practice: LLM Agents with Record & Replay Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 88

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no resolver link, observed 2026-08-07T14:44:30.616295Z

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source=pdf_text observed=2026-08-07T14:44:30.616295Z digest=sha256:6baccca323076e1db10d31965b3156ce0ddd8c4381fe3beb56180c716b5eb189

Observation 0a304c0d-850a-48ab-9d2b-09a464af0328 · outbound

This paper cites Absolute Zero: Reinforced Self-play Reasoning with Zero Data.

Get Experience from Practice: LLM Agents with Record & Replay Absolute Zero: Reinforced Self-play Reasoning with Zero Data

Reference 89

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no resolver link, observed 2026-08-07T14:44:31.034343Z

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source=pdf_text observed=2026-08-07T14:44:31.034343Z digest=sha256:684b7b0a6426a112d24a65144632dddc31cf98b1f45061665f5f91482952afaf

Observation f4e8ea85-a4ae-4260-a115-d904eeb8d472 · outbound

This paper cites UFO2: The Desktop AgentOS.

Get Experience from Practice: LLM Agents with Record & Replay UFO2: The Desktop AgentOS

Reference 90

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no resolver link, observed 2026-08-07T14:44:30.739334Z

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source=pdf_text observed=2026-08-07T14:44:30.739334Z digest=sha256:1e7d9deb29b3791f66364162a4c12e53a400ca1ba14cb303135a1d2a1aca4173

Observation 4e03b32e-bb62-4a96-8b4f-4b971aa5d7b3 · outbound

This paper cites An Empirical Study of Qwen3 Quantization.

Get Experience from Practice: LLM Agents with Record & Replay An Empirical Study of Qwen3 Quantization

Reference 91

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source=pdf_text observed=2026-08-07T14:44:31.192511Z digest=sha256:b6c0a4d0da5572c496142952ce66b4f9bf6a1e6be957f3fe22e6f81dbea0ff11

Observation 8d17247a-c8c3-40db-8060-ac69da1d7cc4 · outbound

This paper cites Explore, Select, Derive, and Recall: Augmenting LLM with Human-like Memory for Mobile Task Automation.

Get Experience from Practice: LLM Agents with Record & Replay Explore, Select, Derive, and Recall: Augmenting LLM with Human-like Memory for Mobile Task Automation

Reference 92

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no resolver link, observed 2026-08-07T14:44:30.927136Z

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source=pdf_text observed=2026-08-07T14:44:30.927136Z digest=sha256:3d8d8a1b77af17799ac13f57fd7e0787b8503c413e52c3783ba57b1674f503c9

Observation 73ce5631-804b-42e7-a0dc-7ac9d5f4e945 · outbound

This paper cites SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks.

Get Experience from Practice: LLM Agents with Record & Replay SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks

Reference 93

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source=pdf_text observed=2026-08-07T14:44:31.351435Z digest=sha256:563ad5ceae32a83563bfa8891fdc628422d064c8459e2a193d9bcb045f80a568

Observation c16780d9-72dd-4c6a-9e28-2a1b35d56b2e · outbound

This paper cites Improving Large Language Model Planning with Action Sequence Similarity.

Get Experience from Practice: LLM Agents with Record & Replay Improving Large Language Model Planning with Action Sequence Similarity

Reference 94

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no resolver link, observed 2026-08-07T14:44:31.124698Z

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source=pdf_text observed=2026-08-07T14:44:31.124698Z digest=sha256:e5a0623924c5813674eb9a4f2e29b14f5245c1d0bfae599eab95358a3c68f548

Observation 2f305c83-0623-425e-b549-0eea3ae05b31 · outbound

This paper cites Agents: An Open-source Framework for Autonomous Language Agents.

Get Experience from Practice: LLM Agents with Record & Replay Agents: An Open-source Framework for Autonomous Language Agents

Reference 96

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source=pdf_text observed=2026-08-07T14:44:31.254713Z digest=sha256:38d651232c821365ecaf0fb70ad5558b790a8f81eb74f93c0dbff68d1ecf38d5

Observation 45cdec95-7520-4ad4-9f20-e75956f887dc · outbound

This paper cites InProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Denver, CO, USA)(SC ’23).

Get Experience from Practice: LLM Agents with Record & Replay InProceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (Denver, CO, USA)(SC ’23)

Reference 2023

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no resolver link, observed 2026-08-07T14:44:27.442200Z

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source=pdf_text observed=2026-08-07T14:44:27.442200Z digest=sha256:1fcf574fa914c354257f0f2a494b4e1b714855483d8b36d8bf3e6e5369681773

Observation 4ce21b4e-fdd7-4e9b-98f7-45ca3d661dbe · outbound

This paper cites Sleep-time Compute: Beyond Inference Scaling at Test-time.

Get Experience from Practice: LLM Agents with Record & Replay Sleep-time Compute: Beyond Inference Scaling at Test-time

Reference 2025

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source=pdf_text observed=2026-08-07T14:44:26.092102Z digest=sha256:5c9d7c7b26f98b45524922418dda698749abbb696f2301c0c9305fc237af6841

Pith citing papers

Observation a68f3fd5-d5fe-40c7-833d-244c3b1f8a82 · inbound

A Survey of Context Engineering for Large Language Models cites this paper.

A Survey of Context Engineering for Large Language Models Get Experience from Practice: LLM Agents with Record & Replay

Reference 281

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verified exact
arxiv_id, observed 2026-05-13T20:58:45.497878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T20:58:45.060041Z digest=sha256:c1c6639e4cb2c22e7e26c17e1023309fc5a782bb622340739329769fae4cae0f

Observation af5c258c-12db-4046-9a0b-41756ddf2f45 · inbound

MobiAgent: A Systematic Framework for Customizable Mobile Agents cites this paper.

MobiAgent: A Systematic Framework for Customizable Mobile Agents Get Experience from Practice: LLM Agents with Record & Replay

Reference 6

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no resolver link, observed 2026-08-05T13:34:58.922731Z

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source=pdf_text observed=2026-08-05T13:34:58.922731Z digest=sha256:3151d6a3a5b61278f9ed6291f9fbd53249af758ac876495488d95d45855c5e8a

Observation 3a5cc48d-7dc9-4d87-8493-617c7b650ea3 · inbound

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory cites this paper.

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory Get Experience from Practice: LLM Agents with Record & Replay

Reference 10

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verified exact
arxiv_id, observed 2026-05-19T16:47:40.526261Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T16:43:37.472644Z digest=sha256:3459990f24a0fca8a3db8103371a118c6646e9faba56fce72b98792e6a45afcf

Observation 72cbed0f-8284-4978-8133-62196e3302b1 · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation Get Experience from Practice: LLM Agents with Record & Replay

Reference 264

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T20:56:13.645618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T17:38:50.313305Z digest=sha256:8d36ae5f04106ebe2a99e5935d678aea78612e583c64aeeceab9521ee5af95ce

Observation db5d8fc0-97db-4219-bac5-83eedb5ecc7a · inbound

PreAct: Computer-Using Agents that Get Faster on Repeated Tasks cites this paper.

PreAct: Computer-Using Agents that Get Faster on Repeated Tasks Get Experience from Practice: LLM Agents with Record & Replay

Reference 11

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verified exact
arxiv_id, observed 2026-07-03T20:58:57.422347Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T01:06:26.643487Z digest=sha256:7d3f15b34e62b4f66ead259a448bcbd243499d9ccad4a0c9d6d86ea6c0673394

Observation 0568d08b-d9df-48df-ab78-090ab505c765 · inbound

HippoSpark: An On-Demand Experience System for LLM Reasoning cites this paper.

HippoSpark: An On-Demand Experience System for LLM Reasoning Get Experience from Practice: LLM Agents with Record & Replay

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:54:21.398181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T06:24:47.449777Z digest=sha256:89787f3daf8135aa0d46c7e2a1cbbbf84fb37191ec803f2e8c3e278a108a6628

Observation a5c8b527-a7d1-4699-85bd-4988962d4dcd · inbound

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) cites this paper.

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) Get Experience from Practice: LLM Agents with Record & Replay

Reference 14

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unresolved
no resolver link, observed 2026-07-31T23:23:44.635925Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:23:44.635925Z digest=sha256:aa8dd4327ae80ba23d93bf9d9ee76e2936d3fbf959b1e950146ce314d09984aa

Observation 6349fc9a-ae93-49e1-ba0f-dcbb0193d5c9 · inbound

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) cites this paper.

Industrial Practice of LLM-Based Test Case Carving and Assertion Generation (Experience Paper) Get Experience from Practice: LLM Agents with Record & Replay

Reference 14

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unresolved
no resolver link, observed 2026-08-04T01:34:38.984471Z

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source=pdf_text observed=2026-08-04T01:34:38.984471Z digest=sha256:2ee81392e0f6bc872a44a41553fb26ede81ce9e0901cd942ef1c0f37da098762