Paper Citation Record · LEDGER

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

As of 23 July 2026, this Paper Citation Record lists 14 of 14 outbound references and 45 inbound Pith citation observations for arXiv:2306.03314.

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

pith.paper-citation-record.v1
2306.03314 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-24T07:48:42.572571Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-23T06:31:01.910684+00:00

measured 45 of 45 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-13T09:27:26.581889Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T20:57:34.363547Z

Reference resolution

14 of 14 outbound references displayed

verified exact1
verified fuzzy13
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ab4c384-c50d-42f5-9664-38b94f9fceaf · outbound

This paper cites Saurous, Jascha Sohl-dickstein, Kevin Murphy, and Charles Sutton.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Saurous, Jascha Sohl-dickstein, Kevin Murphy, and Charles Sutton

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.717518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 2db4c8fd-a2e6-4e1b-b032-d57dd16f205c · outbound

This paper cites O’Brien, Carrie J.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents O’Brien, Carrie J

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.729378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation dc6b6ee5-8e6b-40b8-863e-2f01b58a1147 · outbound

This paper cites Camel: Communicative agents for "mind" exploration of large scale language model society.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Camel: Communicative agents for "mind" exploration of large scale language model society

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.738105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation de544e49-a105-49e0-9891-5e8cd7470ffc · outbound

This paper cites Sparks of artificial general intelligence: Early experiments with gpt-4.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Sparks of artificial general intelligence: Early experiments with gpt-4

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.742488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 49b68b82-cc80-48e4-a41f-39437b253b2f · outbound

This paper cites One small step for generative ai, one giant leap for agi: A complete survey on chatgpt in aigc era.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents One small step for generative ai, one giant leap for agi: A complete survey on chatgpt in aigc era

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.709030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 1f676410-6c6d-4bbe-a03f-8897b27c11c2 · outbound

This paper cites Do, Yan Xu, and Pascale Fung.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Do, Yan Xu, and Pascale Fung

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.733611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation c2e1c71d-6099-439c-9b1b-4f933b922968 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Chain-of-thought prompting elicits reasoning in large language models

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.755710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 1ca330bc-60b6-449b-a85e-4304502b32f9 · outbound

This paper cites Improving language model negotiation with self-play and in-context learning from ai feedback.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Improving language model negotiation with self-play and in-context learning from ai feedback

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.751366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation eb28bacd-e497-4007-b25d-78d0441a84cd · outbound

This paper cites Teaching large language models to self-debug.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Teaching large language models to self-debug

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.703654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 99d165ad-0259-4709-aa20-d15745a88701 · outbound

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

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Self-refine: Iterative refinement with self-feedback

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.725172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 1c0cbe40-bdc9-49ff-bcda-19fe550a6194 · outbound

This paper cites Introducing chatgpt.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Introducing chatgpt

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.746663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 2811aad1-68ce-42d4-877a-97a07f791f8f · outbound

This paper cites Patil, Tianjun Zhang, Xin Wang, and Joseph E.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Patil, Tianjun Zhang, Xin Wang, and Joseph E

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.713482Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 8e43f029-b841-49c5-a094-a92ccf4dbcbe · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents LLaMA: Open and Efficient Foundation Language Models

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-05-24T07:49:08.321041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation dc374ab8-133a-4026-92db-13fdb8cbefc9 · outbound

This paper cites Blind judgement: Agent-based supreme court modelling with gpt.

Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents Blind judgement: Agent-based supreme court modelling with gpt

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-24T07:49:08.697942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Pith citing papers

Observation 8d0279e3-6e5f-4ff0-ae18-57f0fee48817 · inbound

GAIA: a benchmark for General AI Assistants cites this paper.

GAIA: a benchmark for General AI Assistants Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-12T15:46:03.342953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 5f29ccc2-317f-4bc3-a956-fd9ec9663f33 · inbound

LLM Multi-Agent Systems: Challenges and Open Problems cites this paper.

LLM Multi-Agent Systems: Challenges and Open Problems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 46

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T10:23:05.191418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 2a0f0ccd-cf06-4653-b9a0-b97cd71ef384 · inbound

MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data cites this paper.

MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-23T23:53:38.685311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 78a2d323-02c1-454a-a275-d090568840df · inbound

Large Language Model-Based Agents for Software Engineering: A Survey cites this paper.

Large Language Model-Based Agents for Software Engineering: A Survey Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 213

Resolution: verified exact; local_arxiv, observed 2026-05-17T12:35:48.456693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 8ca7bbe8-c8d0-4dc0-8f3d-a645575b4f1c · inbound

Multi-Agent Collaboration Mechanisms: A Survey of LLMs cites this paper.

Multi-Agent Collaboration Mechanisms: A Survey of LLMs Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 120

Resolution: verified exact; arxiv_id, observed 2026-05-13T15:54:54.285642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation bf6b9f6b-54f7-4675-8610-0ef902b0a674 · inbound

Why Do Multi-Agent LLM Systems Fail? cites this paper.

Why Do Multi-Agent LLM Systems Fail? Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:42:58.571343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 5873e2a4-ae3b-48f6-ba2f-c710f20f47b7 · inbound

Language Model Networks: Supervision-Efficient Learning through Dense Communication cites this paper.

Language Model Networks: Supervision-Efficient Learning through Dense Communication Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-05-22T14:51:41.916594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation e0c278fd-10d5-4b80-8016-c3cb8a80ce03 · inbound

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems cites this paper.

From Standalone LLMs to Integrated Intelligence: A Survey of Compound Al Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 169

Resolution: verified exact; local_arxiv, observed 2026-05-19T11:52:16.218686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 6c111b50-d614-44e7-ab27-d316b33ef552 · inbound

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis cites this paper.

GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 109

Resolution: verified exact; local_arxiv, observed 2026-05-22T00:40:51.316693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 4b98ac67-9b4b-45fa-9972-c8777f5f4851 · inbound

A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems cites this paper.

A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-15T23:21:42.719778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation cf304daa-3835-494e-97cc-59b4ce046da6 · inbound

Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents cites this paper.

Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 90

Resolution: verified exact; local_arxiv, observed 2026-05-18T10:11:13.884506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 1aa9c98a-35d2-474a-be5e-55cb038af017 · inbound

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic cites this paper.

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-16T09:50:49.323906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 81a5bc18-6f83-4d75-afa7-f1e2ee9c5768 · inbound

Learning from Self-Debate: Preparing Reasoning Models for Multi-Agent Debate cites this paper.

Learning from Self-Debate: Preparing Reasoning Models for Multi-Agent Debate Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-21T14:30:13.834119Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 817a75d5-b7f2-48ee-ba40-6531b5f79be3 · inbound

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration cites this paper.

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-15T16:40:10.626671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 2c03a470-4810-4e5b-8198-36b31bcfdbee · inbound

Emergent Social Intelligence Risks in Generative Multi-Agent Systems cites this paper.

Emergent Social Intelligence Risks in Generative Multi-Agent Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 119

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:48:00.798543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 89f82f99-ece3-4849-a064-fe1a52ba0c2b · inbound

Scale-free congestion clusters in large-scale traffic networks: a continuum modeling study cites this paper.

Scale-free congestion clusters in large-scale traffic networks: a continuum modeling study Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-13T09:27:26.581889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 719b8603-08dc-435f-9a24-b92eadf851e3 · inbound

LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations cites this paper.

LanG -- A Governance-Aware Agentic AI Platform for Unified Security Operations Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:25:51.450340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation b4b5b516-a79b-481f-a9ea-9d7428243562 · inbound

PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policy cites this paper.

PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policy Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:45:49.298616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation ac9b399c-7b2b-484e-88bc-5fdb8c44c118 · inbound

Aligned Agents, Biased Swarm: Measuring Bias Amplification in Multi-Agent Systems cites this paper.

Aligned Agents, Biased Swarm: Measuring Bias Amplification in Multi-Agent Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T06:51:27.346453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 992299c2-8c95-4f17-a148-0ec1e015f0f9 · inbound

In-situ process monitoring for defect detection in wire-arc additive manufacturing: an agentic AI approach cites this paper.

In-situ process monitoring for defect detection in wire-arc additive manufacturing: an agentic AI approach Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-10T21:20:49.806877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 75b5e116-2617-43bd-beb2-5768728272fa · inbound

Weak-Link Optimization for Multi-Agent Reasoning and Collaboration cites this paper.

Weak-Link Optimization for Multi-Agent Reasoning and Collaboration Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:58:13.243783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation f09746e6-207a-4682-915e-d19947cf2d8f · inbound

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review cites this paper.

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:56:33.836473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 0d555e2f-7420-466e-a531-064eddc483c5 · inbound

HR-Agents: Using Multiple LLM-based Agents to Improve Q&A about Brazilian Labor Legislation cites this paper.

HR-Agents: Using Multiple LLM-based Agents to Improve Q&A about Brazilian Labor Legislation Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-15T11:49:58.728472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation ef0a3160-48c7-4bf3-af06-5a3fdb846208 · inbound

Explicit Trait Inference for Multi-Agent Coordination cites this paper.

Explicit Trait Inference for Multi-Agent Coordination Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T02:53:29.884524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 04044b64-5a51-4ba2-a541-c4d7a2b066ce · inbound

Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization cites this paper.

Learning to Evolve: A Self-Improving Framework for Multi-Agent Systems via Textual Parameter Graph Optimization Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:01:07.035142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 1a1ba22f-bb98-4e7f-824c-fe2b41d5da30 · inbound

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce cites this paper.

EPM-RL: Reinforcement Learning for On-Premise Product Mapping in E-Commerce Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:56:12.709221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 8caa5006-6254-4c8c-9fdd-42406adbbe9e · inbound

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning cites this paper.

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 112

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:35:39.064770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 0b054601-077a-481a-b104-527deeabb094 · inbound

Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs cites this paper.

Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:26:24.449924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation b5fd29cf-fede-485d-a270-e5e09123576e · inbound

A Multi-Agent Framework for Feature-Constrained Difficulty Control in Reading Comprehension Item Generation cites this paper.

A Multi-Agent Framework for Feature-Constrained Difficulty Control in Reading Comprehension Item Generation Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 3

Resolution: metadata mismatch; local_arxiv, observed 2026-05-20T05:58:05.087603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 3ce4e62f-4c46-40ea-8f84-b03d916ededa · inbound

How to Steer Your Multi-Agent System: Human-LLM Collaborative Planning cites this paper.

How to Steer Your Multi-Agent System: Human-LLM Collaborative Planning Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-25T05:05:22.405201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 6fb031f0-fc9d-43ba-bd5a-315c49327f18 · inbound

Traceable Knowledge Graph Reasoning Enables LLM-Assisted Decision Support for Industrial VOCs in the Steel Industry cites this paper.

Traceable Knowledge Graph Reasoning Enables LLM-Assisted Decision Support for Industrial VOCs in the Steel Industry Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-06-29T17:53:47.787376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 27d3ca5a-4e66-43b6-8646-e3baada21f87 · inbound

Decoupled Intelligence: A Multi-Agent LLM Framework for Controllable Traffic Scenario Generation in SUMO cites this paper.

Decoupled Intelligence: A Multi-Agent LLM Framework for Controllable Traffic Scenario Generation in SUMO Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-06-29T14:33:30.400794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 7d6eeb9a-0b1d-4283-9164-49175f4c3311 · inbound

MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsing cites this paper.

MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsing Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-06-29T12:43:26.129040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 5689f6f9-9d84-4e72-aa70-c97d24003e6e · inbound

Bridging Requirements and Architecture: Multi-Agent Orchestration with External Knowledge and Hierarchical Memory cites this paper.

Bridging Requirements and Architecture: Multi-Agent Orchestration with External Knowledge and Hierarchical Memory Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-07-01T21:36:15.856205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 819e717e-cbcb-4e1c-89e2-7a813005aebb · inbound

POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems cites this paper.

POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T23:06:19.955982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 3fc8e211-7506-4a15-b8a8-a6968c4e1c06 · inbound

When Helping Hurts and How to Fix It: Multi-Agent Debate for Data Cleaning cites this paper.

When Helping Hurts and How to Fix It: Multi-Agent Debate for Data Cleaning Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-01T23:36:23.826599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 99a4f9cb-42dd-4d5f-be87-90d372e335d3 · inbound

SHIELDS: Automating OS Hardening with Iterative Multi-Agent Remediation cites this paper.

SHIELDS: Automating OS Hardening with Iterative Multi-Agent Remediation Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 15

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T10:16:52.347695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 12b4d0a0-79ef-4cf9-a226-28771f6da229 · inbound

SkillHone: A Harness for Continual Agent Skill Evolution Through Persistent Decision History cites this paper.

SkillHone: A Harness for Continual Agent Skill Evolution Through Persistent Decision History Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T22:47:26.283392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation ebca56c9-62ed-4bea-9d3b-8bd7376d82a6 · inbound

FASE: Fast Adaptive Semantic Entropy for Code Quality cites this paper.

FASE: Fast Adaptive Semantic Entropy for Code Quality Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-07-03T03:27:35.804324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation cbb5c6a4-97a5-44ee-8232-46ea99189ac3 · inbound

A Lightweight Multi-Agent Framework for Automated Concrete Barrier Design cites this paper.

A Lightweight Multi-Agent Framework for Automated Concrete Barrier Design Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-07-03T11:18:03.611889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation c5c371d3-ac7b-4a5a-9efd-819466771018 · inbound

A Technical Taxonomy of LLM Agent Communication Protocols cites this paper.

A Technical Taxonomy of LLM Agent Communication Protocols Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 12

Resolution: metadata mismatch; local_arxiv, observed 2026-07-04T03:09:28.763677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 4d454a0a-4e03-4199-bc6a-b431d11de73b · inbound

HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualization cites this paper.

HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualization Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 69

Resolution: metadata mismatch; local_arxiv, observed 2026-06-26T03:58:57.731136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 3f66ad56-d987-4071-bf0b-e3314fa5c5f9 · inbound

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model cites this paper.

Safe and Adaptive Cloud Healing: Verifying LLM-Generated Recovery Plans with a Neural-Symbolic World Model Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-07-03T14:58:32.308897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 5da83382-3df8-4c5a-aaf7-c5aa91567828 · inbound

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems cites this paper.

When Agents Go Rogue: Activation-Based Detection of Malicious Behaviors in Multi-Agent Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 59

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T20:57:34.378672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.

Observation 772835de-ed85-4e7e-ac35-a2ef5fc89977 · inbound

Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems cites this paper.

Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems Multi-Agent Collaboration: Harnessing the Power of Intelligent LLM Agents

Reference 88

Resolution: verified exact; local_arxiv, observed 2026-07-10T14:17:10.154341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-23T06:31:01.910684+00:00.