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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:f1d405979ff5754d6fbcf4b249000465b9d892ea2c5c057f25ab752c0e63f94c

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.528161Z digest=sha256:7f137eeb3d54cbb6d6d402912401bb598ef0c73b97fa320a3de06e9bce55ae07

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=sha256:74266fe736fc1df2910aaf1142c303da45850b74f556239c17cc38790cbac555

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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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:eb381239bb6c2fc43c7069a5a866fcc69ba38781e1a6b2ae0b8071968a888786

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:adf5d4def338c4db4cf65f2b9b38ba78f2e126e0fc4feb3960ec8b9c951f763d

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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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=sha256:123bec30619f7e523d209d76fe6aa9d11504620e747baaec10b09b7b7eb35fa6

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.554881Z digest=sha256:f755228b9fcfdf5d6cea3b7138a232a7f04570939fbe24fb88490dde3de9b612

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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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=sha256:2f52ff04a821fb9be6bf07b288aea96b7a54a213b01fd4b8b7ba50d0108d81d7

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.564412Z digest=sha256:cf34649f6e0f4e2ea8314dab54e2d9b733fad4fb876d075280d9659002223112

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=sha256:06494471a9c00848b1bf5b679c45f6fd1824caad3c00f817e75a4713e1e7b6e2

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=sha256:416ec284cf6e402baf286556e1496341e616b7044403931869e8ade3ea9c056a

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=sha256:03dcccf37f12cdb23e31cb412979559695d28c3ec9b73868d4b350a56635db01

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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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:ba88561ebcbef37cb17faa11219931ae15e53d4ce94e146763c43f26c88719e4

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=sha256:257bd73aa9d9d60dae15b33ed6f6f79c7507106fde47015366405184afb9644b

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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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:caf351bb323b72e65a154c5182acf16eee75f100cfe48cb6a98e128cedadec71

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 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-16T10:21:49.599372Z digest=sha256:a73e8e25795c92c89ccf577627f80ac81d69d1a829abea24c2369c39df5e5a85

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=sha256:5787df61f88cbb5f4d26a39606fac1413806b60acccda7bcb4983c0d160b042b

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=sha256:2bd1e774f2c72999e2f273c5c07361040cb7d9f04ad295b9302f0af5554ceba1

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.612806Z digest=sha256:6de1028c577ccca846eda255deb2e47d478e97e88ab48d2574a5528c52d0590e

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.618129Z digest=sha256:ea412334c3fe25f7304882a856b545e1cba619585b755e32548c152bebfdcf8c

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:e7c983d1ce82192ddaeb2e4f913a23dc36240d7bf1ee792f3e86beb89c9beef4

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=sha256:7231230e672e14e9550a11f7d863588a5e5deda4ef73a2ee4424741491ea5658

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=sha256:089f1a8f71bf2ee2ce043e0e9f437304ad34c03d03a496e7d9a0d3c528b5d18b

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=sha256:63255d71791b7398bd0b702e4e17b1d16d294bb37674c8401b71357183ea000a

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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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:dbc3a585d8bf8b089ddebefea50f7b9cd1f313dac04903fe7dc95b61783548b7

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=sha256:61bfe6250923506619988a0e6b127459a5b64805903cf8e2cf6bddb876a7119c

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T10:21:49.651776Z digest=sha256:d55e7ea1da71ba1cf03d551b0337ef49844e18da99373a7cf0bf3c08865905a9

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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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:cfb61d26aa32e5e9c6d0e37480585ea62a2c3499df2282b14cb93fb2a7dbcd6c

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=sha256:5be24d568e1e4e4ea0e6cbd7953ea82698930180dfd80fc3a8ea27980aededdc

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:c5c566c2b13c6873f249509fcfc8455477f36f3fc778338de5c48d76acc54f5d

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=sha256:7163e568051572c892a4c5cb778f42bf83de41871a2fa0d2d2fb4948b3cd2116

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=sha256:7cb0e280cba6fd22d6d13db3ae2e051c4769fdf9d93857b4023274ef155f5b8e

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:d0d5c0e9f29e7d30fd044b57755adf29157fa260be1cbefe46a8c91775e73652

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=sha256:954f693ba67128231edeba5888a28f28ee33f42817c28ec50b09143b2a523713

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:b1a75a44fcbbf02968c9733ca821939d5da0f1ea928143d89b2fef236a3d18e5

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:e408562d345b56ca866deaa083581fd41446ac43e0118aea995fc885dcfafd56

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:ab7bd4571f5aef7f20cb5f57d36abc8615f232c948cf573117cf6f2bd83f3882

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=sha256:43923ca12e92f9b96ee0d621b873ebdf5236d3c73a92b0cf9da392d9ba7550e4

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:eff6ee65a7bce6f018b65b3e8d9f3001939568182f0828a5b1356dac87522f1e

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:c356517938426f095677d1213bd4afb41489fe29447391111fd45950d2c15aab

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=sha256:823ef5c27a795ddaaa93cdb95f3de35249bad655f4beb870aedc96060836db90

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:c2ee0287174c0d334ba025efa4d3beef93547ab57ddec5fbf94985460f9359e9

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=sha256:40229395cd7d7f10db03cb8aa1197120e079f14bbb40bd989232b01dfdff84c8

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:ef77838f392c6667a1c7b8c8ca3fd39a64d71aba566de017aea78188c0fa5f10

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:fc391f27e4e26200c1f77a81061c5b0962edeb0c22ee2fb663d8cc94ec85e5ca

Pith citing papers

No inbound Pith citation observations are available.