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Paper Citation Record · LEDGER

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2504.18373.

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

pith.paper-citation-record.v1
2504.18373 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:21:49.742464Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

45 of 45 outbound references displayed

  • verified exact1
  • verified fuzzy2
  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c156dc7e-6ed6-4b74-91d1-87c78db29521 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 1

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unresolved
raw_fallback, observed 2026-08-16T10:21:50.509931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.522561Z digest=sha256:69f3780aef9d9ff36aec847781ce234a598f1b44b9b0418dfa209936dd7d6c12

Observation 015fdd4d-1705-4e28-8348-9b0c773d601a · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 2

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raw_fallback, observed 2026-08-16T10:21:50.494563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.528161Z digest=sha256:63fe15b49ab9b26c0986284a814400e8562cee7c3a83a6343e9a53d4a23313bc

Observation 4dd197c8-8bc7-4f79-b078-49ee3b715fcb · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 3

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no resolver link, observed 2026-08-16T10:21:49.533166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.533166Z digest=sha256:7882cf20330c8964fad2951f65717ff439a70ff80f79f8d0b332d145a5990fc9

Observation fb5c8bfb-5e45-4792-8afd-476692746c0f · outbound

This paper cites SLURP: A Spoken Language Understanding Resource Package.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant SLURP: A Spoken Language Understanding Resource Package

Reference 4

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unresolved
no resolver link, observed 2026-08-16T10:21:49.538421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.538421Z digest=sha256:7521d6b2de13b9fa5e33a2d048b239c5b4ed0daecfa7303fac2034ea844b5dbf

Observation 34acdfb8-8948-488a-88a4-5fa86552c19e · outbound

This paper cites Karlsson, Jie Fu, and Yemin Shi.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Karlsson, Jie Fu, and Yemin Shi

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-16T10:21:50.468598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.544165Z digest=sha256:1fd724f085414275f21a98e3a7cbca96708663fc92f77788caee7c360086c734

Observation 2c445e23-9c31-4d10-b101-2477def26874 · outbound

This paper cites SocialBench: Sociality Evaluation of Role-Playing Conversational Agents.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant SocialBench: Sociality Evaluation of Role-Playing Conversational Agents

Reference 6

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unresolved
no resolver link, observed 2026-08-16T10:21:49.548950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.548950Z digest=sha256:3afd4da7462db81e6b9d3f59c620fa87d8b510610382ab1625cab3ce37077ab4

Observation b0cc72bf-b43c-4998-97e8-d86b4e65eaca · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 7

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unresolved
raw_fallback, observed 2026-08-16T10:21:50.452158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.554881Z digest=sha256:2ca2e18a7350c5a0466f7d97a62fe6c5e626e3cc4b5d05ab799a3cc560cff500

Observation 85a838aa-2b5d-47c4-b51b-f4cd430916fa · outbound

This paper cites T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Step

Reference 8

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unresolved
no resolver link, observed 2026-08-16T10:21:49.559531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.559531Z digest=sha256:0149441d2fec4d39dfe244b618e725c207d86b92f0f05c3776a5d2601f9fb656

Observation 3c5a4096-ddb7-490b-aaa3-117e728085fa · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-08-16T10:21:50.436560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.564412Z digest=sha256:b61f4e521a91dbc24fa7a36c64721abe96b14efe4c8fba92b2a0741ceeb9b72a

Observation b85ba02a-dc27-494c-a67f-489f9833ec1d · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 10

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raw_fallback, observed 2026-08-16T10:21:50.420907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.569557Z digest=sha256:8891abb4e1ff7e98a39845af1b9521e00ed5d5eefbb754437187c5c7e929c28c

Observation 2641f43a-6fc5-41f5-b9e7-8a8285eb3128 · outbound

This paper cites The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant The ThreeDWorld Transport Challenge: A Visually Guided Task-and-Motion Planning Benchmark for Physically Realistic Embodied AI

Reference 11

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no resolver link, observed 2026-08-16T10:21:49.574221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.574221Z digest=sha256:6df1e1ed5e80c56371ee8f67407a41bb3847f261cb47fae42d9b583f1508d96a

Observation 877ef9a1-0fba-4f1d-b5c8-c344ba955b4b · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 12

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unresolved
no resolver link, observed 2026-08-16T10:21:49.579498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.579498Z digest=sha256:38a2fa62d2e1ea3b4dc5e0b481de3111d1ae3773b659258e00999f73f4949dc9

Observation 5f17253d-2e6e-4977-acb0-51487026adcc · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 13

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unresolved
no resolver link, observed 2026-08-16T10:21:49.584061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.584061Z digest=sha256:e9506461cc3cddc32f060262d270ddc611e4607eb6860796b5fc35ec2705b343

Observation f4fdcbde-831e-43a6-b9d1-f687fa3d11e5 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 14

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unresolved
no resolver link, observed 2026-08-16T10:21:49.589122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.589122Z digest=sha256:f30fb0af234bf7843cc447d9bc157d89a3935e09909e5e38ca4a93dab1f5a99e

Observation 11a6ab6d-8f57-4c2c-8a83-99c17ee45cc1 · outbound

This paper cites Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Dependency Learning for Legal Judgment Prediction with a Unified Text-to-Text Transformer

Reference 15

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unresolved
no resolver link, observed 2026-08-16T10:21:49.594019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.594019Z digest=sha256:ba93ed85e948d9396f14ae92c9794c78e19d90d5cc11e91f58945300888e32f2

Observation 7e0f9369-7e28-444f-bd69-bfc758cc39a4 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 16

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unresolved
raw_fallback, observed 2026-08-16T10:21:50.395005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.599372Z digest=sha256:85cb995a44dfe43241aeb7435b2b49b399917e5ce56996ea42ed8471aa8bfca6

Observation 6e5f86e8-855a-4bdc-acf4-a6343d4775fd · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 17

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raw_fallback, observed 2026-08-16T10:21:50.379226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.603742Z digest=sha256:f0a65d471f45cd8ea1e89765d856fe26d3285cdbd3f8d9047302d7df29506599

Observation 88d105b9-4570-4e9c-bf91-5753b44c2ccb · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-16T10:21:49.608287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.608287Z digest=sha256:1698ad93be0404fd2c763a32ce8891e00a935007abcb49c294d7670862655e03

Observation 0c03efc8-bd85-4918-8bd4-433f24b69ccc · outbound

This paper cites LegalAgentBench: Evaluating LLM Agents in Legal Domain.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant LegalAgentBench: Evaluating LLM Agents in Legal Domain

Reference 19

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unresolved
no resolver link, observed 2026-08-16T10:21:49.612806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.612806Z digest=sha256:dbadcb44d8e5cf6e93216fc4b51cc939297f59ac8befc10c5248cdfc0ebdeec7

Observation 04809457-7820-40d8-a757-9cd31398669a · outbound

This paper cites AgentBench: Evaluating LLMs as Agents.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant AgentBench: Evaluating LLMs as Agents

Reference 20

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unresolved
no resolver link, observed 2026-08-16T10:21:49.618129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.618129Z digest=sha256:d44df00c8cacf25416a1e92848ed7342e55d78da470b6ff522736364188a2b29

Observation 0e7b7072-5e61-4435-ba8a-66e39a48eb5c · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 21

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unresolved
raw_fallback, observed 2026-08-16T10:21:50.353104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.623014Z digest=sha256:e4dd81576864f05f780b2931e1837c9c44a4ccd9f4e34437a9fa2bbb6825d5d3

Observation f6db415f-51f3-4d21-8d4a-0c3bbeeb5618 · outbound

This paper cites AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System

Reference 22

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no resolver link, observed 2026-08-16T10:21:49.627727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.627727Z digest=sha256:4710f9bd0f597c59a4e680bb0dc690e46ddd4737949f444d8c0ad7b95c992989

Observation 4e0e3555-0c4b-4f9c-a788-5509a31e6f93 · outbound

This paper cites AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

Reference 23

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no resolver link, observed 2026-08-16T10:21:49.632677Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.632677Z digest=sha256:362e40d270d40c2011d8520ac59ef8b49432d0bf08262eb0bd1895670f5258f9

Observation 74897ccd-d215-45be-a25c-6e765aa93845 · outbound

This paper cites AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant AgentSense: Benchmarking Social Intelligence of Language Agents through Interactive Scenarios

Reference 24

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no resolver link, observed 2026-08-16T10:21:49.637334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.637334Z digest=sha256:7267d1c04345a00b606f7c5f6ab2a4efb5357f3e519fa4d1ae86eb3bf7264873

Observation 8ffce89e-d73f-495d-bc6c-3539ddb5f646 · outbound

This paper cites Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Watch-And-Help: A Challenge for Social Perception and Human-AI Collaboration

Reference 25

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unresolved
no resolver link, observed 2026-08-16T10:21:49.642253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.642253Z digest=sha256:042d210e8c1a5665b6aab1548ce9f2d68042ae3df6189f23a002be0bad159d2c

Observation 860a4597-4aff-4de8-8921-635bbdd4bdd5 · outbound

This paper cites CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents

Reference 26

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no resolver link, observed 2026-08-16T10:21:49.646995Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.646995Z digest=sha256:38670d46d1f45e8d4bd3c1bbc1187925513887c09837190ae0dcb88014e8124b

Observation 30f61f55-cba1-4e3f-a883-b3206a34dc19 · outbound

This paper cites ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs

Reference 27

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unresolved
no resolver link, observed 2026-08-16T10:21:49.651776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.651776Z digest=sha256:a1349fcc287a1f41c9d2f9de4154f2599369fcea9890c3802ec6deed33ed41df

Observation 65828b5f-b308-497c-8aba-6460a924827f · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 28

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unresolved
raw_fallback, observed 2026-08-16T10:21:50.337117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.657683Z digest=sha256:51dea68c518d04073781d45a4efa29e09826e7482ae187737d5548ad97ebf786

Observation b4443859-4aa1-4012-81a0-67a318826652 · outbound

This paper cites Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Survey.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Low-Resource Dense Retrieval for Open-Domain Question Answering: A Comprehensive Survey

Reference 29

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verified exact
local_arxiv, observed 2026-08-16T10:21:49.885984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.662196Z digest=sha256:cf3ccf56b01be2891f167da2d15b2455c6c3c7af5c2c0471e64acf0d6b770c17

Observation eb57d2ce-ed14-4550-ac75-507f288f3fb1 · outbound

This paper cites Alfworld: Aligning text and embodied environments for interactive learning.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Alfworld: Aligning text and embodied environments for interactive learning

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-16T10:21:50.321635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.666985Z digest=sha256:feaa4ca265d83cc33e09f9ecced68d67f7e1f481161a582b8818e77de253de8d

Observation a9f2111f-9563-4345-8202-27e2c972e4b4 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 31

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raw_fallback, observed 2026-08-16T10:21:50.305262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.671377Z digest=sha256:3b813e6a7bae74f126350528a18978830be0c6d0d45d3e004011203129ee08a5

Observation b888589a-edab-4c13-83c9-95aeadb831cc · outbound

This paper cites Unraveling the Mystery of Scaling Laws: Part I.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unraveling the Mystery of Scaling Laws: Part I

Reference 32

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unresolved
no resolver link, observed 2026-08-16T10:21:49.676047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.676047Z digest=sha256:977f5e6b4215675e938306535dcb48093ae71ba40619dc8cba69f6b7629926e3

Observation 54ca6850-b338-4c94-b88e-acb57778a5e9 · outbound

This paper cites BattleAgentBench: A Benchmark for Evaluating Cooperation and Competition Capabilities of Language Models in Multi-Agent Systems.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant BattleAgentBench: A Benchmark for Evaluating Cooperation and Competition Capabilities of Language Models in Multi-Agent Systems

Reference 33

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unresolved
no resolver link, observed 2026-08-16T10:21:49.681539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.681539Z digest=sha256:8a8630d0d30a838916dc67c3304dbcfd8f944467d75734e9733bd072615c3b08

Observation d34c7846-0827-4394-bdd9-fc5385dcd1e1 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 34

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unresolved
no resolver link, observed 2026-08-16T10:21:49.686442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.686442Z digest=sha256:99caba22f1312f30af7c167b20fc0d1b473eaafbd62d89b8bbc649c7eafaf74d

Observation da51cf25-e026-403e-94b0-021d7af6ea23 · outbound

This paper cites White, Doug Burger, and Chi Wang.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant White, Doug Burger, and Chi Wang

Reference 35

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no resolver link, observed 2026-08-16T10:21:49.691274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.691274Z digest=sha256:87e15197d0a5ebac5ef3f62db599135ad93b082f8b74022c617a745910553446

Observation da0fd5ff-ca9e-4824-84d3-1e5d500f95b3 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 36

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unresolved
raw_fallback, observed 2026-08-16T10:21:50.267655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.696426Z digest=sha256:f35645a694d2f18a5eb18ad097f7a0e5600b908e6554dc437d497830d7b4e26e

Observation 9588de65-7616-4efb-8f96-fdabfd61b7e4 · outbound

This paper cites MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant MAgIC: Investigation of Large Language Model Powered Multi-Agent in Cognition, Adaptability, Rationality and Collaboration

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T10:21:49.700947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.700947Z digest=sha256:116be9bb1777a476cfb917cd374f7856080f5c2510b268679e9269ff91365c77

Observation 3d884cf5-218e-47da-bf2a-9a9c8f64c5a2 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-16T10:21:50.251556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.706236Z digest=sha256:a35c3b86610ffde2fa775fceff19219ed42feba5b47240b9c71e2e645efefb14

Observation 2b4826c8-68ad-4577-a980-ad5f6d85dd6d · outbound

This paper cites ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T10:21:49.710862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.710862Z digest=sha256:2df5cea909d9c080963c395a18bfd44aaf7020c59125c1ef6f34de03f2d4f5b3

Observation a289ea0b-7601-4b88-8f19-cbf8ca91265f · outbound

This paper cites Knowledge-enhanced Session-based Recommendation with Temporal Transformer.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Knowledge-enhanced Session-based Recommendation with Temporal Transformer

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T10:21:49.715495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.715495Z digest=sha256:be812b77551fce3b58752cf2dbfadba5361314ee5d61886a12a40fa2ea37b023

Observation c46572cd-07ab-4574-95ad-8b5e73b72c83 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-16T10:21:49.720901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.720901Z digest=sha256:e77df2e9b5cae79d806549fdf03629e12d578a8300228f718509d0d1a1c036fa

Observation 2b452bd1-b991-4a2a-9189-3a8a484554d1 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-16T10:21:50.224775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.725651Z digest=sha256:8ef090b9512ffda88555c2ac4dda952ebc96970daae457beaa5eb9822a855b94

Observation f5f49c78-7ecd-4ab4-9bfd-5c07af9187b4 · outbound

This paper cites an unresolved cited work.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-16T10:21:50.208632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.731191Z digest=sha256:e61fa1c2229ee35898b97d4a9c3e7e140bcefa875899b47e1e4b48b7368e9c41

Observation 32ad9263-a574-4a58-9895-dd6b0988f1f2 · outbound

This paper cites online" 'onlinestring :=.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant online" 'onlinestring :=

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-16T10:21:49.737029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.737029Z digest=sha256:6a84951a38bd2bda9bc68884d305aecf8ec8c86ce2ff6da1beb8b74e61008af4

Observation d2ba333d-237a-4bfb-b996-5cce6c3d5794 · outbound

This paper cites write newline.

Auto-SLURP: A Benchmark Dataset for Evaluating Multi-Agent Frameworks in Smart Personal Assistant write newline

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-16T10:21:49.742464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.742464Z digest=sha256:0215dfce1e17153561613ef4f23dffbb3f00b1eb609f11e957989b842d4b3a60

Pith citing papers

No inbound Pith citation observations are available.