Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures | Paper Citation Record

Observation c851776e-e6f8-4607-be65-641ef1ca43f6 · outbound

This paper cites Roco: Dialectic multi-robot collabo- ration with large language models.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Roco: Dialectic multi-robot collabo- ration with large language models

Reference 1

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Observation b1f8db00-2e40-4a47-9fee-4f21b1884cf9 · outbound

This paper cites Generative agents: Interactive simulacra of human behavior.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Generative agents: Interactive simulacra of human behavior

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.620767Z

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Observation 91268529-312c-42d4-8911-373f9f7318ab · outbound

This paper cites Internet of satellites (IoS) for intelligent satellite cluster: Applications, methods, and challenges.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Internet of satellites (IoS) for intelligent satellite cluster: Applications, methods, and challenges

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.617539Z

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

Observation d961d146-101c-47d4-9369-990fad28639a · outbound

This paper cites Review on particle swarm optimization: Ap- plication toward autonomous dynamical systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Review on particle swarm optimization: Ap- plication toward autonomous dynamical systems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.473413Z

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Observation 9bd8fd5e-78a8-42af-a70d-2ee9be4972d4 · outbound

This paper cites An overview of recent progress in the study of distributed multi-agent coordination.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures An overview of recent progress in the study of distributed multi-agent coordination

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.493751Z

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Observation 70856823-be05-4a64-b6bc-1cefd50e76bc · outbound

This paper cites The confluence of evolutionary computation and multi-agent systems: A survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures The confluence of evolutionary computation and multi-agent systems: A survey

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.538852Z

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Observation de043607-339f-4cbf-851b-bf8b4fc58cf9 · outbound

This paper cites Multiagent systems: A survey from a machine learning perspective.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Multiagent systems: A survey from a machine learning perspective

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.588569Z

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Observation e6ceaa79-2775-4873-b42f-2161abcfd2f8 · outbound

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

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Multi-Agent Collaboration Mechanisms: A Survey of LLMs

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-13T15:54:55.141401Z

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Observation e0e9ce59-194f-4af6-8066-5c5a57c12d46 · outbound

This paper cites Consensus and coop- eration in networked multi-agent systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Consensus and coop- eration in networked multi-agent systems

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.440639Z

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Observation 3ffb94aa-6d67-45db-93d7-739f5032977d · outbound

This paper cites Multi-agent Reinforcement Learning: A Comprehensive Survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Multi-agent Reinforcement Learning: A Comprehensive Survey

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.089215Z

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Observation fc3dd1bd-3174-4a01-b823-602098aeb439 · outbound

This paper cites Distributed optimal consensus control for multiagent systems based on event-triggered and prioritized experience replay strategies.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Distributed optimal consensus control for multiagent systems based on event-triggered and prioritized experience replay strategies

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.524280Z

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Observation 4b03489b-5f7f-419f-8c94-a5e1966a43c4 · outbound

This paper cites Distributed adaptive formation with state constraints for multi-agent systems: Ne and rne searching in aggregative games.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Distributed adaptive formation with state constraints for multi-agent systems: Ne and rne searching in aggregative games

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.508557Z

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Observation 6b90ce60-0b74-43e7-b43b-7b642c0af271 · outbound

This paper cites Cooperative task scheduling and resource allocation of embodied multi-satellite systems: AI-driven perspective.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Cooperative task scheduling and resource allocation of embodied multi-satellite systems: AI-driven perspective

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.591894Z

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Observation 6ae1cdfd-163a-42eb-8c91-8698d097b4c2 · outbound

This paper cites Swarm intelligence: A review of algorithms.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Swarm intelligence: A review of algorithms

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.585347Z

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

Observation d14fee37-9e74-4ae9-ac8f-41d92d1a8d24 · outbound

This paper cites Applications of multi-agent reinforcement learning in future internet: A comprehensive survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Applications of multi-agent reinforcement learning in future internet: A comprehensive survey

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.549806Z

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Observation 4ae2b308-8d50-4603-80f6-454d91dc3e90 · outbound

This paper cites A Survey of Progress on Cooperative Multi-agent Reinforcement Learning in Open Environment.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A Survey of Progress on Cooperative Multi-agent Reinforcement Learning in Open Environment

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.878341Z

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Observation 13377a4e-8e41-49cd-a153-c096912ee443 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 17

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Observation e112565c-a3ad-4caf-a5f7-e9bad4b131d3 · outbound

This paper cites The rise and potential of large language model based agents: A survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures The rise and potential of large language model based agents: A survey

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.581984Z

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Observation 12e80891-eff5-40b5-b9e0-6c0b1b9dd126 · outbound

This paper cites Large model based agents: State-of-the-art, cooperation paradigms, security and privacy, and future trends.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Large model based agents: State-of-the-art, cooperation paradigms, security and privacy, and future trends

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.469894Z

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Observation d77b307f-945d-4845-a90c-903819501831 · outbound

This paper cites From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review

Reference 20

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Observation 6cfd2365-3932-4510-ad73-d320ceceae59 · outbound

This paper cites Knowledge-empowered, collaborative, and co- evolving AI models: The post-LLM roadmap.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Knowledge-empowered, collaborative, and co- evolving AI models: The post-LLM roadmap

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.558400Z

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Observation 2e0677ef-c984-4342-91ac-3cc70a947423 · outbound

This paper cites The Landscape of Agentic Reinforcement Learning for LLMs: A Survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-11T11:51:03.843942Z

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Observation e5a042f6-0529-4c61-a6ff-c4ce7b63c4d8 · outbound

This paper cites Agentic AI: a com- prehensive survey of architectures, applications, and future directions.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Agentic AI: a com- prehensive survey of architectures, applications, and future directions

Reference 23

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Observation c31cca49-0676-4e30-9b70-7711b831931d · outbound

This paper cites A survey on the optimization of large language model-based agents.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A survey on the optimization of large language model-based agents

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.852538Z

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Observation 63a717b5-aef5-4fcb-ac2e-5fadf5ffda8d · outbound

This paper cites LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures LLM-based Agentic Reasoning Frameworks: A Survey from Methods to Scenarios

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.757068Z

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

Observation de377832-16a3-45a6-9e90-bd246c8d06b5 · outbound

This paper cites Wooldridge,An introduction to multiagent systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Wooldridge,An introduction to multiagent systems

Reference 26

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Observation 1446cf73-711b-446e-9a5e-ff7179354c25 · outbound

This paper cites Computer vision tasks for intelli- gent aerospace perception: An overview.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Computer vision tasks for intelli- gent aerospace perception: An overview

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.554632Z

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Observation 41b75d8c-2131-43df-970c-187b2d2a0bf4 · outbound

This paper cites Cooper: Cooperative perception for connected autonomous vehicles based on 3D point clouds.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Cooper: Cooperative perception for connected autonomous vehicles based on 3D point clouds

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.532110Z

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

Observation fd834b2e-7b20-4d7b-82a3-5974d30c75d8 · outbound

This paper cites Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Dair-v2x: A large-scale dataset for vehicle- infrastructure cooperative 3d object detection

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.578001Z

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

Observation cdcb3e43-78dd-4e12-8374-df6b066eb93f · outbound

This paper cites Mmcooper: A multi-agent multi-stage communication-efficient and collaboration-robust cooperative perception framework.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Mmcooper: A multi-agent multi-stage communication-efficient and collaboration-robust cooperative perception framework

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.512626Z

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 f6e4680a-3106-4f1c-8c85-b5ef6698407e · outbound

This paper cites A novel fusion attention-based lightweight model for pipeline weld multiscale defect detection.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A novel fusion attention-based lightweight model for pipeline weld multiscale defect detection

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.501335Z

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

Observation 10b22383-6b49-48bf-86c7-15e1e5b871f2 · outbound

This paper cites Spatio-temporal domain awareness for multi-agent col- laborative perception.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Spatio-temporal domain awareness for multi-agent col- laborative perception

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.466216Z

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

Observation 14f72365-9e7e-4448-8117-b5eadcd196f4 · outbound

This paper cites Multi-agent collaborative perception via motion-aware robust communication network.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Multi-agent collaborative perception via motion-aware robust communication network

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.517079Z

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 8efdf59d-8d8d-42c5-9c82-5aeb2de0c085 · outbound

This paper cites Pragmatic heterogeneous collaborative perception via generative communication mechanism.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Pragmatic heterogeneous collaborative perception via generative communication mechanism

Reference 34

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

Observation 23f69374-590e-4b97-9add-1bbe68510ff6 · outbound

This paper cites Multi-Agent Coordination across Diverse Applications: A Survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Multi-Agent Coordination across Diverse Applications: A Survey

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.065816Z

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

Observation 1d1bf9fd-3a04-43bd-bc54-bc81c1f3f86c · outbound

This paper cites Network topology and information efficiency of multi-agent systems: Study based on marl.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Network topology and information efficiency of multi-agent systems: Study based on marl

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.766812Z

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

Observation 00321f66-c906-4a27-a8b4-d4794a6525bc · outbound

This paper cites Robust multi- agent communication with graph information bottleneck optimization.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Robust multi- agent communication with graph information bottleneck optimization

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.451638Z

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

Observation af3b5f15-0ef8-407b-ae44-9cbc300eb598 · outbound

This paper cites Event-triggered communication network with limited-bandwidth constraint for multi- agent reinforcement learning.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Event-triggered communication network with limited-bandwidth constraint for multi- agent reinforcement learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.462237Z

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

Observation d4ca2933-cbde-4b24-a71c-c8861495dd0f · outbound

This paper cites Event-triggered attitude synchro- nization of multiple rigid body systems with velocity-free measure- ments.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Event-triggered attitude synchro- nization of multiple rigid body systems with velocity-free measure- ments

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.432321Z

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 ba853254-204e-4dc5-9526-44f1b7da496f · outbound

This paper cites Event-triggered fixed-time attitude consensus with fixed and switching topologies.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Event-triggered fixed-time attitude consensus with fixed and switching topologies

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.504775Z

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 35aedb91-d5ad-4333-931d-5854f9b6b9e1 · outbound

This paper cites Learning to communicate through implicit communication channels.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Learning to communicate through implicit communication channels

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.424907Z

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 e928e370-1a94-4ad4-b69c-1ee558a55a01 · outbound

This paper cites A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.872609Z

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 1240c172-1c7c-4270-b8a1-918c7716f753 · outbound

This paper cites Cooperative multi-agent learning: The state of the art.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Cooperative multi-agent learning: The state of the art

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.489663Z

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 c0757708-56f9-4816-81d5-e06d9bf8846a · outbound

This paper cites Distributed nash equilibrium for pursuit-evasion game with one evader and multiple pursuers.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Distributed nash equilibrium for pursuit-evasion game with one evader and multiple pursuers

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.562257Z

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 6ce34864-0b03-4b57-bcfa-b8cc7fda38fe · outbound

This paper cites Recent advances in consensus of multi-agent systems: A brief survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Recent advances in consensus of multi-agent systems: A brief survey

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.607108Z

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 07dd6d68-9202-4b36-898f-9419db5dc141 · outbound

This paper cites Consensus in multi-agent systems: a review.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Consensus in multi-agent systems: a review

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.428275Z

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 82bb151e-ecee-4aaa-a0c0-9e0dfec88af7 · outbound

This paper cites Consensus seeking in multiagent systems under dynamically changing interaction topologies.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Consensus seeking in multiagent systems under dynamically changing interaction topologies

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.570028Z

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 991743d1-2d67-4df3-8406-34d220bfc836 · outbound

This paper cites Synchronizing linear systems via partial-state coupling.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Synchronizing linear systems via partial-state coupling

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.481199Z

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 2e6cbb1c-fe0c-43e6-951e-e2a0360cdd27 · outbound

This paper cites Distributed consensus for multiagent systems with communication delays and limited data rate.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Distributed consensus for multiagent systems with communication delays and limited data rate

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.447742Z

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 cacff16e-fe67-425a-9f19-296918b0e145 · outbound

This paper cites Observer-based consensus control for mass with prescribed constraints via reinforcement learning algorithm.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Observer-based consensus control for mass with prescribed constraints via reinforcement learning algorithm

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.528420Z

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 461ff33b-e254-4a40-a95b-1e0146ee57dd · outbound

This paper cites Adaptive prescribed- time dynamic self-triggered time-varying bipartite formation control for uncertain nonlinear multiagent systems with actuator faults.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Adaptive prescribed- time dynamic self-triggered time-varying bipartite formation control for uncertain nonlinear multiagent systems with actuator faults

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.477560Z

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 12e7d8a9-d435-45d2-a4ff-828a13a5db53 · outbound

This paper cites A survey of multi-agent formation control.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A survey of multi-agent formation control

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.485910Z

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 16784a08-4322-4a08-9599-5b7c871ae6ea · outbound

This paper cites Robust formation control for co- operative underactuated quadrotors via reinforcement learning.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Robust formation control for co- operative underactuated quadrotors via reinforcement learning

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.444278Z

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 cde4e9f8-94e5-402b-93de-fc8cfd15d3ef · outbound

This paper cites A brief overview of chatgpt: The history, status quo and potential future development.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A brief overview of chatgpt: The history, status quo and potential future development

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.565978Z

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 329228a9-9ab7-47b1-a81c-1eb0cfdfe7fb · outbound

This paper cites Deepseek: paradigm shifts and technical evolution in large ai models.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Deepseek: paradigm shifts and technical evolution in large ai models

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.610776Z

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 85bd8c70-158c-49d9-9d41-5441d8e0a3c9 · outbound

This paper cites ChatDev: Communicative Agents for Software Development.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures ChatDev: Communicative Agents for Software Development

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-12T20:32:47.766951Z

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 895acedf-8708-43a8-96bb-456caafc80a6 · outbound

This paper cites Metagpt: Meta programming for a multi-agent col- laborative framework.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Metagpt: Meta programming for a multi-agent col- laborative framework

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.064901Z

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 9afc8548-d7d3-49de-968d-08d692715de1 · outbound

This paper cites Automated Design of Agentic Systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Automated Design of Agentic Systems

Reference 58

Resolution: verified exact; arxiv_id, observed 2026-05-15T08:07:55.640311Z

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 6a61b1b1-6b03-4528-8521-9af1ea3ac4a8 · outbound

This paper cites The virtual lab of AI agents designs new sars-cov-2 nanobodies.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures The virtual lab of AI agents designs new sars-cov-2 nanobodies

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.068327Z

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 cb4efba3-07c6-46bb-a853-e82d4bbeba40 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.058173Z

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 18e3cc61-50a4-45b9-9c4e-c422795be0f6 · outbound

This paper cites Deep residual learning for image recognition.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Deep residual learning for image recognition

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.047846Z

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 f41271dd-4f09-44b1-82e4-ef901d0db8f6 · outbound

This paper cites Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.897961Z

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 f3142070-c82f-41f8-8957-2cedf36b4c35 · outbound

This paper cites Agent planning with world knowledge model.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Agent planning with world knowledge model

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.603615Z

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 65caa6b7-3233-41e0-9084-8b1b20d656ab · outbound

This paper cites PlanGenLLMs: A Modern Survey of LLM Planning Capabilities.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures PlanGenLLMs: A Modern Survey of LLM Planning Capabilities

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.725137Z

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 04642062-ce35-4560-bcf8-d6c0fb76da1f · outbound

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

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Chain-of-thought prompting elicits reasoning in large language models

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.054704Z

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 71c0dcd7-1cd8-4f6f-a02e-1f0a4d3c0a5d · outbound

This paper cites A survey on the feedback mechanism of LLM- based AI agents.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A survey on the feedback mechanism of LLM- based AI agents

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.614417Z

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 3661fe79-6acc-47af-ba81-0e4032d38cd9 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 67

Resolution: verified exact; local_arxiv, observed 2026-05-11T11:51:03.721553Z

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 98d120de-a7d3-4b72-9b9d-6d86a6463642 · outbound

This paper cites Recommender AI agent: Integrating large language models for interactive recommen- dations.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Recommender AI agent: Integrating large language models for interactive recommen- dations

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.535678Z

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 1ca6fc58-3e6c-4e57-8838-d1c02e458222 · outbound

This paper cites Isr-llm: Iterative self-refined large language model for long-horizon sequential task planning.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Isr-llm: Iterative self-refined large language model for long-horizon sequential task planning

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.600036Z

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 29d94bbd-7169-4a71-9c86-05ae5ab5a8f2 · outbound

This paper cites Monte Carlo Planning with Large Language Model for Text-Based Game Agents.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Monte Carlo Planning with Large Language Model for Text-Based Game Agents

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:51:03.714474Z

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 16e14a55-a915-442d-a14d-7004f4275eb9 · outbound

This paper cites Agentgen: Enhancing planning abilities for large language model based agent via environment and task generation.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Agentgen: Enhancing planning abilities for large language model based agent via environment and task generation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.034334Z

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 6ca4d3da-3b32-4a9d-82fc-9258a6989fef · outbound

This paper cites Machine memory intelligence: Inspired by human memory mechanisms.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Machine memory intelligence: Inspired by human memory mechanisms

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.037843Z

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 1fbacb3d-6048-4bf7-be9b-68032b1d3138 · outbound

This paper cites A survey on the memory mechanism of large language model-based agents.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A survey on the memory mechanism of large language model-based agents

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.024002Z

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 38fbf569-948a-4821-9a06-21e623117d97 · outbound

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

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures ReAct: Synergizing Reasoning and Acting in Language Models

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-05-11T11:51:03.808967Z

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 5f9facaf-d121-46ef-b868-1c6cde11a48c · outbound

This paper cites Expel: LLM agents are experiential learners.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Expel: LLM agents are experiential learners

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.041220Z

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 847ed282-a3af-419f-923c-4bee95e4fbcf · outbound

This paper cites From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Users

Reference 76

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.697431Z

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 3a60be20-1fff-4167-90e3-161c057ff5dc · outbound

This paper cites Hugginggpt: Solving AI tasks with chatgpt and its friends in hugging face.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Hugginggpt: Solving AI tasks with chatgpt and its friends in hugging face

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.520775Z

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 a797a02b-4dd1-4f74-bed9-ffd5b5310af3 · outbound

This paper cites Gorilla: Large language model connected with massive apis.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Gorilla: Large language model connected with massive apis

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:06.985690Z

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 f6ee03a8-27f7-469c-929c-6a7bb3a9a049 · outbound

This paper cites Multi-agent Embodied AI: Advances and Future Directions.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Multi-agent Embodied AI: Advances and Future Directions

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.700674Z

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 32284052-6725-449e-a6a3-38e96dff8efa · outbound

This paper cites Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Reference 80

Resolution: verified exact; arxiv_id, observed 2026-05-14T00:00:16.565169Z

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 7e2ffe92-fbc1-46ec-8bf2-f94ff28127bd · outbound

This paper cites Removal of Hallucination on Hallucination: Debate-Augmented RAG.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Removal of Hallucination on Hallucination: Debate-Augmented RAG

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.731342Z

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 47cbd74a-75e4-468e-9180-78401661199d · outbound

This paper cites CGMI: Configurable General Multi-Agent Interaction Framework.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures CGMI: Configurable General Multi-Agent Interaction Framework

Reference 82

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:51:04.081303Z

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 7b809596-55cf-4557-9568-636656b81c59 · outbound

This paper cites SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.860530Z

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 afd7bc30-0e15-45f5-b9b1-7d3d6e1cfcd7 · outbound

This paper cites ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Tasks

Reference 84

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.061560Z

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 412e21bd-a250-410e-8380-3956db309f80 · outbound

This paper cites AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML

Reference 85

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.071865Z

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 7778085d-ba7e-4cf0-88a1-1d9b08b4af35 · outbound

This paper cites Stochastic self- organization in multi-agent systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Stochastic self- organization in multi-agent systems

Reference 86

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.026936Z

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 2dc2f754-2220-45d1-a6a4-a63741f5b4db · outbound

This paper cites Mas 2: Self-generative, self-configuring, self-rectifying multi-agent systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Mas 2: Self-generative, self-configuring, self-rectifying multi-agent systems

Reference 87

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.016881Z

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 06829ae6-1dde-49f4-8661-29720658f6b3 · outbound

This paper cites Beyond Self-Talk: A Communication-Centric Survey of LLM-Based Multi-Agent Systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Beyond Self-Talk: A Communication-Centric Survey of LLM-Based Multi-Agent Systems

Reference 88

Resolution: verified exact; arxiv_id, observed 2026-05-27T02:04:27.865242Z

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 fa0418c1-181e-4f08-a3aa-8c00a9818f5d · outbound

This paper cites Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems

Reference 89

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.051057Z

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 c972dc1f-74d2-484a-a8df-7aa62c240207 · outbound

This paper cites AgentDropout: Dynamic Agent Elimination for Token-Efficient and High-Performance LLM-Based Multi-Agent Collaboration.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures AgentDropout: Dynamic Agent Elimination for Token-Efficient and High-Performance LLM-Based Multi-Agent Collaboration

Reference 90

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:51:03.800435Z

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 f4c24b09-578d-4642-9df0-5618a7f5b653 · outbound

This paper cites Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Proactive Agent: Shifting LLM Agents from Reactive Responses to Active Assistance

Reference 91

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.748936Z

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 ae96871c-22aa-4f8f-af42-3b65c65c4908 · outbound

This paper cites Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interface.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Interactive Speculative Planning: Enhance Agent Efficiency through Co-design of System and User Interface

Reference 92

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.785345Z

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 c73a2109-d815-423c-894c-033b8f5ba57f · outbound

This paper cites InThe F ourteenth International Conference on Learning Representations.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures InThe F ourteenth International Conference on Learning Representations

Reference 93

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:51:03.828117Z

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 89fc223d-2962-413c-b83a-58408c719fb2 · outbound

This paper cites A Survey of LLM-based Agents in Medicine: How far are we from Baymax?.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures A Survey of LLM-based Agents in Medicine: How far are we from Baymax?

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:03.796157Z

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 de5bfea7-02df-47f9-99ac-0257342067d1 · outbound

This paper cites Context-aware collaborative pushing of heavy objects using skeleton-based intention prediction.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Context-aware collaborative pushing of heavy objects using skeleton-based intention prediction

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:56:05.456675Z

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 7ac8479d-164b-45d0-8a93-98438979cc6c · outbound

This paper cites Instruction tuning for large language models: A survey.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Instruction tuning for large language models: A survey

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T04:51:07.013195Z

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 f4cf9952-ad33-4e9f-8c30-89926b88acc9 · outbound

This paper cites RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:13:34.687091Z

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 9fd0703a-1567-401e-bd35-c85bc0c31ec3 · outbound

This paper cites OS-Kairos: Adaptive Interaction for MLLM-Powered GUI Agents.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures OS-Kairos: Adaptive Interaction for MLLM-Powered GUI Agents

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.045590Z

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 80e94209-9660-4f03-9d68-3a17f887eee7 · outbound

This paper cites AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures AgentGym-RL: Training LLM Agents for Long-Horizon Decision Making through Multi-Turn Reinforcement Learning

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:51:04.003863Z

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 99b6cb2c-e8b0-427c-9e6f-a91abd6a64e5 · outbound

This paper cites Agent Lightning: Train ANY AI Agents with Reinforcement Learning.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures Agent Lightning: Train ANY AI Agents with Reinforcement Learning

Reference 100

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:51:03.991797Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers