Training Small LLMs as Spatial Multi-Agent Policies | Paper Citation Record

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This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

Training Small LLMs as Spatial Multi-Agent Policies Voyager: An Open-Ended Embodied Agent with Large Language Models

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Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

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Training Small LLMs as Spatial Multi-Agent Policies arXiv preprint arXiv:2601.17152 , year=

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Training Small LLMs as Spatial Multi-Agent Policies OpenReview , year=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems , volume=

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Training Small LLMs as Spatial Multi-Agent Policies arXiv preprint arXiv:2510.01586 , year=

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This paper cites Closed-Loop Vision-Language Planning for Multi-Agent Coordination.

Training Small LLMs as Spatial Multi-Agent Policies Closed-Loop Vision-Language Planning for Multi-Agent Coordination

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Training Small LLMs as Spatial Multi-Agent Policies UC Santa Barbara , year=

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This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Training Small LLMs as Spatial Multi-Agent Policies Understanding R1-Zero-Like Training: A Critical Perspective

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems , volume=

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This paper cites Proximal Policy Optimization Algorithms.

Training Small LLMs as Spatial Multi-Agent Policies Proximal Policy Optimization Algorithms

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Training Small LLMs as Spatial Multi-Agent Policies International Conference on Machine Learning , pages=

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Training Small LLMs as Spatial Multi-Agent Policies NeurIPS Workshop on Foundation Models for Decision Making , year=

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Training Small LLMs as Spatial Multi-Agent Policies Proceedings of the AAAI Conference on Artificial Intelligence , year=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems (NeurIPS) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Proceedings of the AAAI Conference on Artificial Intelligence , volume=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems (NeurIPS) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems (NeurIPS) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems (NeurIPS) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Springer , year=

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Training Small LLMs as Spatial Multi-Agent Policies LoRA: Low-Rank Adaptation of Large Language Models

Reference 24

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Training Small LLMs as Spatial Multi-Agent Policies International Conference on Machine Learning , year=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems , volume=

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Training Small LLMs as Spatial Multi-Agent Policies MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

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Training Small LLMs as Spatial Multi-Agent Policies ACL , year=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems , volume=

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Training Small LLMs as Spatial Multi-Agent Policies and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu , booktitle=

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Training Small LLMs as Spatial Multi-Agent Policies Ghost in the Minecraft: Generally Capable Agents for Open-World Environments via Large Language Models with Text-based Knowledge and Memory

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Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

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Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

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Training Small LLMs as Spatial Multi-Agent Policies International Conference on Learning Representations (ICLR) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Conference on Robot Learning (CoRL) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Conference on Robot Learning (CoRL) , year=

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Training Small LLMs as Spatial Multi-Agent Policies IEEE International Conference on Robotics and Automation (ICRA) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Efficient Guided Generation for Large Language Models

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems (NeurIPS) , year=

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Training Small LLMs as Spatial Multi-Agent Policies 2025 , note=

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Training Small LLMs as Spatial Multi-Agent Policies Advances in Neural Information Processing Systems (NeurIPS) , year=

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Training Small LLMs as Spatial Multi-Agent Policies and Chandar, Sarath and Burch, Neil and Lanctot, Marc and Song, H

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Training Small LLMs as Spatial Multi-Agent Policies Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS) , year=

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Training Small LLMs as Spatial Multi-Agent Policies and Griffiths, Thomas L

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Training Small LLMs as Spatial Multi-Agent Policies Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST) , year=

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Training Small LLMs as Spatial Multi-Agent Policies and Precup, Doina and Singh, Satinder , journal=

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Training Small LLMs as Spatial Multi-Agent Policies Proceedings of the AAAI Conference on Artificial Intelligence , volume=

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Training Small LLMs as Spatial Multi-Agent Policies International Conference on Learning Representations (ICLR) , year=

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Training Small LLMs as Spatial Multi-Agent Policies Planning with Macro-Actions in Decentralized

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Training Small LLMs as Spatial Multi-Agent Policies Proceedings of the 3rd Conference on Robot Learning (CoRL) , series =

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6fa2ef9f-167e-4585-883b-af4bfbf96553 · outbound

This paper cites Melting Pot 2.0.

Training Small LLMs as Spatial Multi-Agent Policies Melting Pot 2.0

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.036828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4446c246-3a87-4cab-8a68-bba161cd121a · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:20.144954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ca5ef68b-b704-4e09-b427-a00fb561974a · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 67

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:20.129244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 37a23397-6dbb-4921-98ba-c35f6f86013b · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 68

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:20.112323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation be1ee015-6b03-40fa-8258-0f241e4d48e2 · outbound

This paper cites K.; Griffiths, T.

Training Small LLMs as Spatial Multi-Agent Policies K.; Griffiths, T

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:17:20.095697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f51176cd-a51d-4833-92ac-0f9649304b43 · outbound

This paper cites Beyond Scalar Rewards: Dense Feedback for LLM Policy Synthesis in Sequential Social Dilemmas.

Training Small LLMs as Spatial Multi-Agent Policies Beyond Scalar Rewards: Dense Feedback for LLM Policy Synthesis in Sequential Social Dilemmas

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.064587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 074dcf2b-4495-4183-9722-abe3ed2c6eb1 · outbound

This paper cites J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W.

Training Small LLMs as Spatial Multi-Agent Policies J.; Shen, Y.; Wallis, P.; Allen-Zhu, Z.; Li, Y.; Wang, S.; Wang, L.; and Chen, W

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:17:20.079512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6e6c1218-4dcb-43f3-96ef-eef2c6215eec · outbound

This paper cites Shapley-Coop: Credit Assignment for Emergent Cooperation in Self-Interested LLM Agents.

Training Small LLMs as Spatial Multi-Agent Policies Shapley-Coop: Credit Assignment for Emergent Cooperation in Self-Interested LLM Agents

Reference 72

Resolution: verified exact; local_arxiv, observed 2026-08-06T00:17:19.440446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c3d2e64b-13ae-4f2b-9695-637cb1ae01da · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 73

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:20.063475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5f08f481-6680-4341-8cc4-ff7a8559f6f3 · outbound

This paper cites Z.; Phillips, M.; Tuyls, K.; Du \'e \ n ez-Guzm \'a n, E.

Training Small LLMs as Spatial Multi-Agent Policies Z.; Phillips, M.; Tuyls, K.; Du \'e \ n ez-Guzm \'a n, E

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:17:20.047296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4e82f720-32cc-46fc-bd4a-9162abb3a677 · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.093339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b0df47a-78fc-41e5-9a9d-ef91e1a0e6ac · outbound

This paper cites Z.; Zambaldi, V.; Lanctot, M.; Marecki, J.; and Graepel, T.

Training Small LLMs as Spatial Multi-Agent Policies Z.; Zambaldi, V.; Lanctot, M.; Marecki, J.; and Graepel, T

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:17:20.030609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4ef82487-1800-488d-8341-243b57cc5ee5 · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:20.013919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9fb159ba-b3df-4cd0-b1b3-dfc0ae6029be · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.109264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b9ef1fc-705d-4fcb-b573-359e092ebda6 · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:19.996489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 393301f8-4665-4d83-9de7-38482675db31 · outbound

This paper cites S.; Rios, M.; Fonseca, Y.; Giraldo, L.

Training Small LLMs as Spatial Multi-Agent Policies S.; Rios, M.; Fonseca, Y.; Giraldo, L

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:17:19.975414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c5f27482-1d88-405c-9225-5ccec37cbaf9 · outbound

This paper cites Z.; Zambaldi, V.; Beattie, C.; Tuyls, K.; and Graepel, T.

Training Small LLMs as Spatial Multi-Agent Policies Z.; Zambaldi, V.; Beattie, C.; Tuyls, K.; and Graepel, T

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:17:19.958505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a032285e-e12f-460b-8ab8-5d5fd80d6392 · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.131642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23aee3d0-7425-4fee-b340-f63ba4738826 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Training Small LLMs as Spatial Multi-Agent Policies DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.136940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf7d81a3-36db-414c-ad10-6dcefc65d953 · outbound

This paper cites S.; Precup, D.; and Singh, S.

Training Small LLMs as Spatial Multi-Agent Policies S.; Precup, D.; and Singh, S

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T00:17:19.941061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a35f7338-3833-459b-9157-b94ed8552733 · outbound

This paper cites On the Planning Abilities of Large Language Models : A Critical Investigation.

Training Small LLMs as Spatial Multi-Agent Policies On the Planning Abilities of Large Language Models : A Critical Investigation

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.146958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 177a0a35-6a89-47ef-9c81-af255d2df0de · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:19.924618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 34d0d686-e323-4f85-ad92-f58c18a118ed · outbound

This paper cites Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning.

Training Small LLMs as Spatial Multi-Agent Policies Low-Rank Agent-Specific Adaptation (LoRASA) for Multi-Agent Policy Learning

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-06T00:17:19.157771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 747efd9e-4ff6-476a-82c9-b01992e752e3 · outbound

This paper cites an unresolved cited work.

Training Small LLMs as Spatial Multi-Agent Policies Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-06T00:17:19.906827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers