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Paper Citation Record · LEDGER

LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2405.11106.

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

pith.paper-citation-record.v1
2405.11106 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:10:24.540443Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ffd589cf-8436-4a2b-a609-4c1ba1740507 · inbound

Large Language Model-Brained GUI Agents: A Survey cites this paper.

Large Language Model-Brained GUI Agents: A Survey LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 51

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verified exact
arxiv_id, observed 2026-05-19T11:08:28.017293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-19T11:08:27.472508Z digest=sha256:0651ba51b4b99495f8d2673b81fcc4431d9c27cd2745a266aa916cdcf31c36ba

Observation 52332e50-919e-4ff0-9509-22f09a427e1e · inbound

A Decade of Deep Learning: A Survey on The Magnificent Seven cites this paper.

A Decade of Deep Learning: A Survey on The Magnificent Seven LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 2019

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no resolver link, observed 2026-08-11T16:10:24.540443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:10:24.540443Z digest=sha256:6e7a3cc33643c9946af7f78b97f7ae263455b67cbb16536b2e79d8f73f85f346

Observation f535b46f-9eb4-4442-a6bc-ff709572bfe2 · inbound

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches cites this paper.

Large language models for artificial general intelligence (AGI): A survey of foundational principles and approaches LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 212

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no resolver link, observed 2026-08-10T21:56:12.841718Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:56:12.841718Z digest=sha256:86f844675f57e35340d62e6913c4425d3d3b2f3c1184ba750c09cbdf837882e7

Observation 894dd2f0-27e6-4eda-8a62-48e2df8eb747 · inbound

LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models cites this paper.

LLM-MedQA: Enhancing Medical Question Answering through Case Studies in Large Language Models LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 7

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no resolver link, observed 2026-08-10T22:49:31.958953Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-10T22:49:31.958953Z digest=sha256:00ff558dda70a869b77754ed2e85e8c9f0a70f3c3b9f00de97c684b0878b338b

Observation 61f93453-9e4e-4792-a08a-e298c07da7a6 · inbound

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

Multi-Agent Collaboration Mechanisms: A Survey of LLMs LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 118

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arxiv_id, observed 2026-05-13T15:54:54.272152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-13T15:54:54.146003Z digest=sha256:f2347c29d55ccf9436752f30df41910150625e129fb3fafe64d1a0b0cea3b073

Observation 33fe289c-27b1-48f6-bff1-57e016643d53 · inbound

STMA: A Spatio-Temporal Memory Agent for Long-Horizon Embodied Task Planning cites this paper.

STMA: A Spatio-Temporal Memory Agent for Long-Horizon Embodied Task Planning LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 35

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no resolver link, observed 2026-08-07T19:10:00.146972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:10:00.146972Z digest=sha256:6a2494f5a40ee9d76d892d951490107d8e6410237f432c4b8ec5de47fb46bb70

Observation 8ebe0ff7-0c27-46a3-8e56-958debc7e8f8 · inbound

From Virtual Agents to Robot Teams: A Multi-Robot Framework Evaluation in High-Stakes Healthcare Context cites this paper.

From Virtual Agents to Robot Teams: A Multi-Robot Framework Evaluation in High-Stakes Healthcare Context LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 51

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no resolver link, observed 2026-08-07T11:05:22.527201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:05:22.527201Z digest=sha256:33126e36c3f2c5dbdac678b2d6470a051de16fbe2b0701131cff27e9cced7354

Observation 6dfa02b4-64d2-4034-907e-24d1ff83c84a · inbound

MasHost Builds It All: Autonomous Multi-Agent System Directed by Reinforcement Learning cites this paper.

MasHost Builds It All: Autonomous Multi-Agent System Directed by Reinforcement Learning LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 29

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no resolver link, observed 2026-08-07T05:15:46.313451Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:15:46.313451Z digest=sha256:d2d905b079bcaf0e63bd635792bb0d0be0885723da07eadffb66c39e91df0fee

Observation a1f76433-9b2a-45fa-8d74-ed3c8261d4c1 · inbound

RALLY: Role-Adaptive LLM-Driven Yoked Navigation for Agentic UAV Swarms cites this paper.

RALLY: Role-Adaptive LLM-Driven Yoked Navigation for Agentic UAV Swarms LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 43

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no resolver link, observed 2026-08-06T21:02:33.207487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:02:33.207487Z digest=sha256:ee12e286c0d578d7dc35bf90239208a6c16d64416009952b1968f5e83c796a08

Observation 003568f4-bc90-4abd-ba59-6c8b11e9ba29 · inbound

WebSailor: Navigating Super-human Reasoning for Web Agent cites this paper.

WebSailor: Navigating Super-human Reasoning for Web Agent LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 18

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arxiv_id, observed 2026-05-17T15:37:09.712100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-17T15:37:09.572241Z digest=sha256:5da2b647c2f96f9b5958a7ef92ced2e348dad604ddb152b54a17dd1bde2cda7c

Observation 85482870-44a4-4f09-822f-316d2cf3f20c · inbound

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 125

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arxiv_id, observed 2026-05-14T22:23:15.856569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-14T22:23:14.621091Z digest=sha256:07252dbd757d602f8ab422c1aabb0899e2abe5d49285bbc7ad6f78d53a9fde1c

Observation fabc8d4a-808d-47a5-a9f6-17af5f205a5f · inbound

LLM-Driven Policy Diffusion: Enhancing Generalization in Offline Reinforcement Learning cites this paper.

LLM-Driven Policy Diffusion: Enhancing Generalization in Offline Reinforcement Learning LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 2022

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no resolver link, observed 2026-08-05T13:46:02.788254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:46:02.788254Z digest=sha256:68e7d1b11e98784a238ccd2126583d215345fb2c58b6e18eb5cbc35e46a9ee3c

Observation b6f36d5c-56ce-427c-b255-cd2b859afd21 · inbound

A Survey of the State-of-the-Art in Conversational Question Answering Systems cites this paper.

A Survey of the State-of-the-Art in Conversational Question Answering Systems LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 68

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no resolver link, observed 2026-08-05T05:11:23.150380Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:11:23.150380Z digest=sha256:c8e60d7b1033111f715fc93c53c9fcb20ffbe2a39e786af68f38300ae967ae1d

Observation 372fa8f8-d5dd-4ae9-9150-6eac6627c569 · inbound

Adaptive Obstacle-Aware Task Assignment and Planning for Heterogeneous Robot Teaming cites this paper.

Adaptive Obstacle-Aware Task Assignment and Planning for Heterogeneous Robot Teaming LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 27

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arxiv_id, observed 2026-05-18T06:41:00.563951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-18T06:38:24.695002Z digest=sha256:c2e2475bc3178d53a640907ff78e8f23fee41b3ab5feae04c99ebeb2c9918cb8

Observation a79c6109-ad03-40be-85dd-c06562f1f2e7 · inbound

Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents cites this paper.

Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 2

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arxiv_id, observed 2026-05-16T18:33:15.280434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-16T18:32:01.569665Z digest=sha256:d0d147370ab339bcd14f209b577b5c1806abbf713f92df1525d1fe2865240c12

Observation bb1d87e6-2825-4d45-9ca8-e2197dcb73b7 · inbound

Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents cites this paper.

Agentic Memory: Learning Unified Long-Term and Short-Term Memory Management for Large Language Model Agents LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 2024

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no resolver link, observed 2026-08-03T12:45:05.696276Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T12:45:05.696276Z digest=sha256:bc7c024aff1cca58d0d847b87a1346ed657a111bff4f524223ea113bb556058e

Observation 45508f44-d710-45e9-bd5d-5a2d02df45e5 · inbound

Joint Optimization of Multi-agent Memory System cites this paper.

Joint Optimization of Multi-agent Memory System LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 26

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verified exact
arxiv_id, observed 2026-05-15T12:15:34.604330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-15T12:12:35.056095Z digest=sha256:94fe180ec23b158b2a2dd8defea3ddb434584d263c75cf0e48791aa93a6af590

Observation 397440b8-dd14-462a-a9ab-5249f6538543 · inbound

CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution cites this paper.

CoEvolve: Training LLM Agents via Agent-Data Mutual Evolution LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 2

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arxiv_id, observed 2026-05-10T09:08:27.138711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T08:06:29.467987Z digest=sha256:ecd2123b5910bae3a1fa3e055829bd482b43b3d9458f5bcee7265d9bf997918a

Observation b6176c7e-de33-4803-9b7a-c001c63ab2b5 · inbound

Do LLM-derived graph priors improve multi-agent coordination? cites this paper.

Do LLM-derived graph priors improve multi-agent coordination? LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 34

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arxiv_id, observed 2026-05-10T06:11:20.213591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T06:09:08.100187Z digest=sha256:93101d3014530289de281a72eedb8681b24d0c2dbfbdc1c3544231f11c53b4bb

Observation 1a223834-cc8a-4e71-b107-2c9564581554 · inbound

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures cites this paper.

Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 131

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arxiv_id, observed 2026-05-11T11:51:03.815274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-10T04:31:28.242097Z digest=sha256:c3f1c6a7cb000226779f57b39f2cfe8aae9312423598257d21fd391dfaa16f60

Observation 74ac8ecf-caab-4893-8287-bfa7872dd406 · inbound

Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning cites this paper.

Robust Instruction Compliance in Cooperative Multi-Agent Reinforcement Learning LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 48

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arxiv_id, observed 2026-06-30T22:15:05.737340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-30T22:11:35.277901Z digest=sha256:c93667aacd5fe7169c33c29199db923f6ee658427a5f1e8559e40d55386eb5f5

Observation 153ca3c2-f869-454f-ba54-cb13aa871ed0 · inbound

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning cites this paper.

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 33

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arxiv_id, observed 2026-05-20T22:53:49.364775Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-20T22:51:56.666980Z digest=sha256:843be208c47350d8f94ac1727ec7b6abbc154f2513c1125de1c715e8bc7f9144

Observation 71033bfd-bc23-4bd3-b91e-9ef02af06b6d · inbound

Multi-Agent Coordination Adaptation via Structure-Guided Orchestration cites this paper.

Multi-Agent Coordination Adaptation via Structure-Guided Orchestration LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 6

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arxiv_id, observed 2026-06-29T19:43:54.922885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-29T19:36:42.234848Z digest=sha256:07eb1a793251f95a2e65b73946c1d4aa55cf86174341f9fe9985549e3da1ae3c

Observation aae5e59c-699b-44fc-801a-cdd5a662ea25 · inbound

Deep-Unfolded Coordination cites this paper.

Deep-Unfolded Coordination LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 6

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arxiv_id, observed 2026-07-04T04:19:34.375856Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-26T17:05:44.372648Z digest=sha256:f117da110a3464ecb6c3e0636d510e5e94a8dbf142c0d47b8222f4ca2df3adba

Observation 8f191f63-7402-4817-8025-0b843c6c6b89 · inbound

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG cites this paper.

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 131

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no resolver link, observed 2026-08-02T10:20:56.162142Z

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source=arxiv_source observed=2026-08-02T10:20:56.162142Z digest=sha256:01e2679e0b471e1456ac5c977180556b835e268d75e69061ad1f0af24a2d0d3f

Observation af0f901d-63e3-437d-8aaf-44a05f9fdcb4 · inbound

A MARL Centered Reference Architecture for Large Language Model Augmentation in Smart Manufacturing cites this paper.

A MARL Centered Reference Architecture for Large Language Model Augmentation in Smart Manufacturing LLM-based Multi-Agent Reinforcement Learning: Current and Future Directions

Reference 32

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no resolver link, observed 2026-08-10T14:00:57.546457Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:00:57.546457Z digest=sha256:4f4f8d683a833f9535912fbc09c8ea3a59880f457251cfac9f1a6a544b914a6b