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Paper Citation Record · LEDGER

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

As of 23 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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.522561Z digest=sha256:31b4542acfa508ae680c7a8e0f5933edc652c417e63b6de52057b900f8c3340a

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.528161Z digest=sha256:c99e8212cd6550645d20aeb61e41c7f6b805c77a50ada472c66af56451e9cf9b

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=sha256:6935811c8fcc24a027a065b8a89522c88e003b32b09fab953b1beb78c17d7b65

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=sha256:5ca59cfb64b5f5cf80633c991ca2d973f41779db98b044eac47e9030111db39b

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

Resolution
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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.544165Z digest=sha256:a940a9f68006745da36123acbb136fd2d182cd3cf012d13a529626800368f877

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=sha256:505bc29b6df4dc4bcd0cd13e46544d2157f04b2d63f120d502209707cb24630f

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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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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.554881Z digest=sha256:7abd2c0cc5a029bf060e53415709018022fed93eb2d59f9b7b58d8969c265c77

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=sha256:7cd205ef9ceaaf58fdfcf25e978bb977be681ae55ed9ef02395a4daa6d61c018

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

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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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.564412Z digest=sha256:6340d3cb64f260c6ccfe89c80218144fd77633c8d81921162d999aece1f5ecf8

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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unresolved
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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.569557Z digest=sha256:a2b661cc5e036906dbfd5cba3c5f93ff327b7fd21f3d41ea4dbe8cffa5bdfc1d

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=sha256:5e61c1edb4604ecc0ed8ecb61b20956ac8d7a2e30d99f7d7800673d8c78a5afc

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=sha256:9c30a11da17aa11b34782a356bbc6260220103b61a6b181f72cde952b9343774

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=sha256:29cc3c576c588fc4f1456a1b0d67a1d7db87d2eac9a757b18f92813597789529

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:eb3780dffa1becb9095a5125401c441a03c86461ccdfc194fcc0c9be347f25f7

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.594019Z digest=sha256:0182698b4d6462d092859533a70af61e455819639e56274456258a16e8e9088c

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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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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.599372Z digest=sha256:83d9664bb058157b38d17668bac060a781d85335708799a6b0f810c0e6d3c355

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.603742Z digest=sha256:61c0286314de580f6d76a8a9fa0e0419c3068a571ddcb899cb4924487ab932f1

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=sha256:73e0a65579aafeaab1e3b33b826cd5312331ed26a45e9729ede64e71c686e3b1

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:b3b493200188b68c70fdc6b9593fe468c3656319c879622805d930675cc1bf4b

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=sha256:1fcd5fb55e81e126b36b63073d685a7bcefa323b59daa0d62f8445aaae70b28c

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.623014Z digest=sha256:e469c78366fd11d03cd2fa92d142e587693e9f344b075374b65276c3e9d35c4b

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=sha256:1c3688e46a9a5a9892650c44ab11de77f43eec30b55047a1116ef3ef91bff993

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=sha256:767bcd91cbd53d3102e0339444aa0600d3af066a818ca8d743b2ddd08858c62e

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=sha256:0fee993805f2614e890194efdf3925cada7e55301c6c9925e52590f174fcf489

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.642253Z digest=sha256:92bbc3b468ff867cb65931568b42ad0a652242024b05b58f448cb807b5411057

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=sha256:3f79bbd514f1edea13fa032ba4ea46e6c16df68b654c3dcfaacb170950958c54

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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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=sha256:7bb35391f43775b91dfc322aef4713b99cf5c1c6087af99cf835a0d8d8e14682

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.657683Z digest=sha256:b25a5cb2ace80c5ac64d400fd4e9a80666bf80e93094281c345fe293e5d40680

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.662196Z digest=sha256:218932193b1c564ec6bf66fdf813e501c24cd821167fc920690205d18798c49c

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.666985Z digest=sha256:d5b9132e3eb058ed75d3da5df8f7ced27420cf3fa51dd358d19b4cf15bbd5fc8

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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unresolved
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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.671377Z digest=sha256:8a1855d118096adb4537e659f25e20050da819f9d87c3cbe667e36088806c5d0

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=sha256:9f483f9ebc37c66b82983b5a23092fe6efe33bc1f1dc6b261b9c9767252db87c

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:ca7068f75d8bf90d63876bd4ccd3c416e4209221ab1933643d67c8d1b0d927b8

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:c03005f8f5ae3b821751c1af5076b08184c1ba7eaf0f7520e20aa48135873346

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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unresolved
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=sha256:790b1716e0790be54a35503c177b829effdecb915addb251cd650a55b5ed0159

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.696426Z digest=sha256:809ae5513c25f635672ff1f2820bc0c687ee476950d7030ff45695c3a2332425

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:f87535d3a085a56ac97be2ae8a2ca9ebb3747bc75b0b5ffaedb5d512dcbfa5e4

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.706236Z digest=sha256:05933a66eb1f657d1a690161d21ab49a029e3f2d0ff686a6b4f24e14631cdf51

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:fc33755f59b9f4f0c4fe0c9d2315e6ea51c2995d320e1f55f4148e6652353af8

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:af84940da72fafb5b5b57ff64ad8b5c65b4fb5bf917f725bfdf3227f255c00a4

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=sha256:3f64675a89324a1c28f3da611af74607287b1efb2be78855d15513f4df15015c

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.725651Z digest=sha256:fa37783d5cd6164d629cf37dfac26edebe240267fdf0cb5e3743d771df3abbdd

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 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.731191Z digest=sha256:f5e56bba5bc8ac2a38720771800aeedf2ec8ca28398a0f692eb0ca1125063fd8

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:b32c9b6f32a8f6f7e6238e81b1f53a39b898887d9f91638f35b5eba6b2424d51

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=sha256:6c80ad2c6ce246613c659a1f4e8bfae102185a586727d814e2ed9d937f2367e6

Pith citing papers

No inbound Pith citation observations are available.