Benchmarking Open-Ended Multi-Agent Coordination in Language Agents | Paper Citation Record

Observation f7a5f70c-ba09-48b8-ac61-afd210f3f65b · outbound

This paper cites Melting Pot 2.0.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Melting Pot 2.0

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-02T22:07:25.837587Z

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Observation 50d813f5-5692-4c5d-bd47-706b88e236c0 · outbound

This paper cites Deep reinforcement learning at the edge of the statistical precipice.Advances in Neural Information Processing Systems, 2021.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Deep reinforcement learning at the edge of the statistical precipice.Advances in Neural Information Processing Systems, 2021

Reference 2

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Observation b59aa67e-4c3e-4ef6-9122-dcf7dc512583 · outbound

This paper cites Llm-coordination: evaluating and analyzing multi-agent coordination abilities in large language models.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Llm-coordination: evaluating and analyzing multi-agent coordination abilities in large language models

Reference 3

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Observation 8db17a47-ad0b-4236-b701-0bae4c2f5bc4 · outbound

This paper cites The hanabi challenge: A new frontier for ai research.Artificial Intelligence, 280:103216, 2020.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The hanabi challenge: A new frontier for ai research.Artificial Intelligence, 280:103216, 2020

Reference 4

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Observation 803e569b-d1ab-4ba3-94b6-bc9fddcb0dcc · outbound

This paper cites The arcade learning environment: An evaluation platform for general agents.Journal of artificial intelligence research, 47:253–279, 2013.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The arcade learning environment: An evaluation platform for general agents.Journal of artificial intelligence research, 47:253–279, 2013

Reference 5

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Observation c514a66b-27d8-4ed0-af8e-14ce846ac99e · outbound

This paper cites JAX: composable transformations of Python+NumPy programs, 2018.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents JAX: composable transformations of Python+NumPy programs, 2018

Reference 6

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Observation 26c9b99c-9012-4622-a9d5-e36cf6f0ae91 · outbound

This paper cites Superhuman ai for heads-up no-limit poker: Libratus beats top professionals.Science, 359(6374):418–424, 2018.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Superhuman ai for heads-up no-limit poker: Libratus beats top professionals.Science, 359(6374):418–424, 2018

Reference 7

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Observation 2c1b7b02-577f-4e52-ae4d-07d4ed26a3f6 · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901, 2020

Reference 8

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Observation 3220a018-d7c7-4453-864a-b777d31e1d42 · outbound

This paper cites Deep blue.Artificial intelligence, 134(1-2):57–83, 2002.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Deep blue.Artificial intelligence, 134(1-2):57–83, 2002

Reference 9

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Observation 847bc0f1-5d20-4c7d-bc1c-256753e091e3 · outbound

This paper cites On the utility of learning about humans for human-ai coordination.Advances in neural information processing systems, 32, 2019.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents On the utility of learning about humans for human-ai coordination.Advances in neural information processing systems, 32, 2019

Reference 10

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Observation eef40610-6b56-42f6-bcb7-caf2542005c9 · outbound

This paper cites MLE-bench: Evaluating machine learning agents on machine learning engineering.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents MLE-bench: Evaluating machine learning agents on machine learning engineering

Reference 11

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Observation 25717b9d-3024-4e1f-be48-7c30eb504949 · outbound

This paper cites Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?

Reference 12

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Observation 022147d5-e39f-4f92-a6fe-d46d39ef1861 · outbound

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

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 13

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Observation 6135fc64-bbc0-45cb-a220-e6507f5fa373 · outbound

This paper cites Improv- ing factuality and reasoning in language models through multiagent debate.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Improv- ing factuality and reasoning in language models through multiagent debate

Reference 14

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Observation a1bdd995-3ba6-4820-9b00-385280459451 · outbound

This paper cites Smacv2: An improved benchmark for cooperative multi-agent reinforcement learning.Advances in Neural Information Processing Systems, 36:37567–37593, 2023.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Smacv2: An improved benchmark for cooperative multi-agent reinforcement learning.Advances in Neural Information Processing Systems, 36:37567–37593, 2023

Reference 15

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Observation 4b2b49d0-aace-4643-834d-4def46249717 · outbound

This paper cites Simplifying deep temporal difference learning.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Simplifying deep temporal difference learning

Reference 16

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Observation f0b3de9c-05b8-4e14-8dce-40942b4e84fa · outbound

This paper cites Overcookedv2: Rethinking overcooked for zero-shot coordination.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Overcookedv2: Rethinking overcooked for zero-shot coordination

Reference 17

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Observation 763b77cd-2070-4a74-88b2-85bf9692f2af · outbound

This paper cites Gemini 3.1 pro model card.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Gemini 3.1 pro model card

Reference 18

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Observation ac242237-0a68-44d5-881c-fcc2c989b991 · outbound

This paper cites Gemma 4 model card.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Gemma 4 model card

Reference 19

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Observation ed9eee9c-c55a-4f6d-8bad-2081d0459431 · outbound

This paper cites KellyBench: A Benchmark for Long-Horizon Sequential Decision Making.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents KellyBench: A Benchmark for Long-Horizon Sequential Decision Making

Reference 20

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Observation 7a87bf2f-8fab-406b-878b-458a0116a3fd · outbound

This paper cites The Llama 3 Herd of Models.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The Llama 3 Herd of Models

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:07:25.834809Z

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Observation 7fea0335-8c3f-4c5b-a5e3-6f1af02faf90 · outbound

This paper cites AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs

Reference 22

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Observation cb811d90-d298-45cc-9c56-231bf212d622 · outbound

This paper cites Large language model based multi-agents: a survey of progress and challenges.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Large language model based multi-agents: a survey of progress and challenges

Reference 23

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Observation 2a159151-40fd-4730-b126-e7f4f75c37c3 · outbound

This paper cites Benchmarking the spectrum of agent capabilities.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Benchmarking the spectrum of agent capabilities

Reference 24

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This paper cites Multi-Agent Risks from Advanced AI.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Multi-Agent Risks from Advanced AI

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:57:25.939633Z

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Observation 8103005f-0ba4-451f-b42e-564e88c0f201 · outbound

This paper cites Dynamic programming for partially observable stochastic games.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Dynamic programming for partially observable stochastic games

Reference 26

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This paper cites YC-Bench : Benchmarking AI agents for long-term planning and consistent execution.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents YC-Bench : Benchmarking AI agents for long-term planning and consistent execution

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:57:25.942643Z

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Observation d42b5e69-1652-4223-9b57-095a253cbf05 · outbound

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

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Metagpt: Meta programming for a multi-agent collaborative framework

Reference 28

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Observation 2954ecfb-c452-4f81-beb9-d58126a60d2a · outbound

This paper cites Position: Open-endedness is essential for artificial superhuman intelligence.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Position: Open-endedness is essential for artificial superhuman intelligence

Reference 29

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Observation 00930267-5a84-40ed-864c-64ba1f10a56d · outbound

This paper cites GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents GPUDrive: Data-driven, multi-agent driving simulation at 1 million FPS

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Observation 11c58ef6-bf05-4360-8048-055cc3656be6 · outbound

This paper cites Measuring AI Ability to Complete Long Software Tasks.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Measuring AI Ability to Complete Long Software Tasks

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Observation cb55698a-3642-4f69-a387-ebad98254270 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Efficient memory management for large language model serving with pagedattention

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Observation 3231cd7d-1a90-49ba-a6ac-8b504e7f6514 · outbound

This paper cites Scalable evaluation of multi-agent reinforcement learning with melting pot.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Scalable evaluation of multi-agent reinforcement learning with melting pot

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Observation a0b1e157-6a7b-47d7-ab2f-72a9963c013c · outbound

This paper cites Stateful active facilitator: Co- ordination and environmental heterogeneity in cooperative multi-agent reinforcement learn- ing.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Stateful active facilitator: Co- ordination and environmental heterogeneity in cooperative multi-agent reinforcement learn- ing

Reference 34

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This paper cites Towards end-to-end automation of ai research.Nature, 651(8107):914–919, 2026.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Towards end-to-end automation of ai research.Nature, 651(8107):914–919, 2026

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This paper cites The interdisciplinary study of coordination.ACM Computing Surveys (CSUR), 26(1):87–119, 1994.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The interdisciplinary study of coordination.ACM Computing Surveys (CSUR), 26(1):87–119, 1994

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This paper cites Craftax: A lightning-fast benchmark for open-ended reinforcement learning.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Craftax: A lightning-fast benchmark for open-ended reinforcement learning

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This paper cites The influence of scaffolds on coordination scaling laws in LLM agents.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The influence of scaffolds on coordination scaling laws in LLM agents

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Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Unresolved cited work

Reference 39

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This paper cites WebGPT: Browser-assisted question-answering with human feedback.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents WebGPT: Browser-assisted question-answering with human feedback

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Resolution: verified exact; local_arxiv, observed 2026-07-02T21:57:26.474953Z

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Observation 7045ef07-23ee-41f0-960c-2a54d2f7f4a1 · outbound

This paper cites Multi- agent craftax: Benchmarking open-ended multi-agent reinforcement learning at the hyperscale.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Multi- agent craftax: Benchmarking open-ended multi-agent reinforcement learning at the hyperscale

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This paper cites Introducing gpt-5.4.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Introducing gpt-5.4

Reference 42

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This paper cites BALROG: Benchmarking agentic LLM and VLM reasoning on games.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents BALROG: Benchmarking agentic LLM and VLM reasoning on games

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Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Unresolved cited work

Reference 44

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This paper cites Qwen3.6-Plus: Towards real world agents, April 2026.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Qwen3.6-Plus: Towards real world agents, April 2026

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This paper cites Jaxmarl: Multi-agent rl environments and algorithms in jax.Advances in Neural Information Processing Systems, 37:50925–50951, 2024.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Jaxmarl: Multi-agent rl environments and algorithms in jax.Advances in Neural Information Processing Systems, 37:50925–50951, 2024

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Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Unresolved cited work

Reference 47

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This paper cites Harvard university press, 1980.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Harvard university press, 1980

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This paper cites Mastering atari, go, chess and shogi by planning with a learned model.Nature, 588(7839):604–609, 2020.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Mastering atari, go, chess and shogi by planning with a learned model.Nature, 588(7839):604–609, 2020

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Observation 2f382997-0879-47c2-9126-2cbad57a8a90 · outbound

This paper cites The illusion of thinking: Understanding the strengths and limitations of reasoning models via the lens of problem complexity.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The illusion of thinking: Understanding the strengths and limitations of reasoning models via the lens of problem complexity

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This paper cites The illusion of diminishing returns: Measuring long horizon execution in LLMs.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The illusion of diminishing returns: Measuring long horizon execution in LLMs

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Observation f25956c3-aaa5-4824-9764-fbe7fcad84bc · outbound

This paper cites Cambridge University Press, 2004.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Cambridge University Press, 2004

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Observation fae28ccf-f4c9-4696-a22f-fa22e3edcdd3 · outbound

This paper cites Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Neural MMO: A Massively Multiagent Game Environment for Training and Evaluating Intelligent Agents

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Resolution: verified exact; local_arxiv, observed 2026-07-02T21:57:26.480037Z

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Observation 40972b0c-6593-462d-ba9b-1334d739ad61 · outbound

This paper cites Neural mmo 2.0: a massively multi-task addition to massively multi-agent learning.Advances in Neural Information Processing Systems, 36:50094–50104, 2023.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Neural mmo 2.0: a massively multi-task addition to massively multi-agent learning.Advances in Neural Information Processing Systems, 36:50094–50104, 2023

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This paper cites Collab-overcooked: Benchmarking and evaluating large language models as collaborative agents.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Collab-overcooked: Benchmarking and evaluating large language models as collaborative agents

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Observation 1e7e5c25-6426-41dd-aed2-1e926467d02a · outbound

This paper cites Qwen3.5: Accelerating productivity with native multimodal agents, February.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Qwen3.5: Accelerating productivity with native multimodal agents, February

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Observation 19d16a19-f1bd-4a6c-88c6-095781dc2e74 · outbound

This paper cites an unresolved cited work.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Unresolved cited work

Reference 57

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e23311f-45df-46a4-af54-b6879e8a4fdf · outbound

This paper cites Hypermarl: Adaptive hypernetworks for multi-agent rl.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Hypermarl: Adaptive hypernetworks for multi-agent rl

Reference 58

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99b49b6b-a53a-45ef-9b26-ab105b49b0a2 · outbound

This paper cites Probing dec-POMDP reasoning in cooperative MARL.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Probing dec-POMDP reasoning in cooperative MARL

Reference 59

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f88a188-cc22-4713-a1aa-dc06d4ebe76a · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 60

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e385151-8669-4fd3-8c19-063af38846e0 · outbound

This paper cites Grandmaster level in starcraft ii using multi-agent reinforcement learning.nature, 575(7782):350–354, 2019.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Grandmaster level in starcraft ii using multi-agent reinforcement learning.nature, 575(7782):350–354, 2019

Reference 61

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12aef7d2-b64b-44cb-858d-10f963bccb3c · outbound

This paper cites V oyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research, 2024.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents V oyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research, 2024

Reference 62

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54db5e46-b1ba-41bb-82a2-6991ed0d43bc · outbound

This paper cites BattleAgentBench: A Benchmark for Evaluating Cooperation and Competition Capabilities of Language Models in Multi-Agent Systems.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents BattleAgentBench: A Benchmark for Evaluating Cooperation and Competition Capabilities of Language Models in Multi-Agent Systems

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:57:26.483468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 2fb866c7-3830-4bb4-b3fb-a9ecb1dd1d5a · outbound

This paper cites OdysseyBench: Evaluating LLM Agents on Long-Horizon Complex Office Application Workflows.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents OdysseyBench: Evaluating LLM Agents on Long-Horizon Complex Office Application Workflows

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:57:26.489813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cb41eca6-8e69-42cd-b10a-5246adfd5b41 · outbound

This paper cites The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-07-02T21:57:26.492973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 268c12ed-7f4c-4f93-a7f8-a60d6bbb6580 · outbound

This paper cites LLM- powered decentralized generative agents with adaptive hierarchical knowledge graph for co- operative planning.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents LLM- powered decentralized generative agents with adaptive hierarchical knowledge graph for co- operative planning

Reference 66

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 519dafca-3ff6-448c-a57a-f305f7f4144c · outbound

This paper cites React: Synergizing reasoning and acting in language models.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents React: Synergizing reasoning and acting in language models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 043edb4e-f88b-4561-a60c-2f835456b35f · outbound

This paper cites An Efficient Open World Environment for Multi-Agent Social Learning.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents An Efficient Open World Environment for Multi-Agent Social Learning

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:57:26.477512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 65f49f67-45dd-44b8-acdc-022a66b3e71c · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games.Advances in neural information processing systems, 35:24611–24624, 2022.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The surprising effectiveness of ppo in cooperative multi-agent games.Advances in neural information processing systems, 35:24611–24624, 2022

Reference 69

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cc8f711-ba8f-4f87-abde-556685233499 · outbound

This paper cites Yinger Zhang, Shutong Jiang, Renhao Li, Jianhong Tu, Yang Su, Lianghao Deng, Xudong Guo, Chenxu Lv, and Junyang Lin.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Yinger Zhang, Shutong Jiang, Renhao Li, Jianhong Tu, Yang Su, Lianghao Deng, Xudong Guo, Chenxu Lv, and Junyang Lin

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T21:57:25.945763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 23c1e0b0-0674-4e00-888f-1ae0fe52be74 · outbound

This paper cites AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents AMA-Bench: Evaluating Long-Horizon Memory for Agentic Applications

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:07:25.841029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 5be93d94-2e6f-484e-8c63-3d311130b72f · outbound

This paper cites Multiagentbench: Evaluating the collaboration and competition of llm agents.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Multiagentbench: Evaluating the collaboration and competition of llm agents

Reference 72

Resolution: malformed identifier; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c93ba9b5-378b-43f3-bcaf-26a3b6d9c128 · outbound

This paper cites By default it also optionally includes the full action catalogue with natural-language descriptions, game and coordination mechanics.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents By default it also optionally includes the full action catalogue with natural-language descriptions, game and coordination mechanics

Reference 73

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7aa8abb5-ca0c-4529-9124-7295b191e3d1 · outbound

This paper cites Observation from k step(s) ago.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Observation from k step(s) ago

Reference 74

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f96908de-3996-4cbb-abe3-a9e558bcc3d1 · outbound

This paper cites The agent is then prompted to respond with an action.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The agent is then prompted to respond with an action

Reference 75

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 686764f3-2877-49a3-a676-07e2aae58d08 · outbound

This paper cites an unresolved cited work.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Unresolved cited work

Reference 76

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d25e8562-2e63-4b6b-bd42-07e8474d4c1e · outbound

This paper cites an unresolved cited work.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Unresolved cited work

Reference 77

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fb18d4c-5910-40fb-913e-01172986b31e · outbound

This paper cites The ladder only becomes usable after enough monsters on that level have been killed.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents The ladder only becomes usable after enough monsters on that level have been killed

Reference 78

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 222ddb51-b827-4e46-92d8-581257202220 · outbound

This paper cites an unresolved cited work.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Unresolved cited work

Reference 79

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b25005e-4955-47b8-af2b-951272fa3635 · outbound

This paper cites Teammates can only act on what you tell them.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents Teammates can only act on what you tell them

Reference 80

Resolution: unresolved; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe74fa9e-167e-482e-8370-86032dbbc114 · outbound

This paper cites TN: ” or “TurnN:.

Benchmarking Open-Ended Multi-Agent Coordination in Language Agents TN: ” or “TurnN:

Reference 81

Resolution: malformed identifier; no resolver link, observed 2026-06-27T19:18:56.039587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

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Outbound references

Pith citing papers