Paper Citation Record · LEDGER

Double Distillation Network for Multi-Agent Reinforcement Learning

As of 14 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2502.03125.

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

pith.paper-citation-record.v1
2502.03125 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:54:06.573779Z

measured 29 of 29 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

29 of 29 outbound references displayed

verified exact0
verified fuzzy17
unresolved12
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 48f5fa52-df87-417b-8141-0b7224d97926 · outbound

This paper cites Exploration by Random Network Distillation.

Double Distillation Network for Multi-Agent Reinforcement Learning Exploration by Random Network Distillation

Reference 1

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Source-reported events for the cited work

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Observation 552fff4d-4135-4836-968b-14c081cbb5d4 · outbound

This paper cites The learning rate for the neural networks is uniformly set to 5 × 10−4.

Double Distillation Network for Multi-Agent Reinforcement Learning The learning rate for the neural networks is uniformly set to 5 × 10−4

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.641532Z

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.

Observation 1404e1d8-62a7-4700-9fcd-17ae18856a99 · outbound

This paper cites Multi-agent reinforcement learning as a rehearsal for decentralized planning.

Double Distillation Network for Multi-Agent Reinforcement Learning Multi-agent reinforcement learning as a rehearsal for decentralized planning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.761427Z

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Observation e687fb5f-3da2-484f-baf3-f2e3aa1980ba · outbound

This paper cites A review of cooperative multi-agent deep reinforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning A review of cooperative multi-agent deep reinforcement learning

Reference 10

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Source-reported events for the cited work

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Observation b5b26b8c-dd7d-4921-ac1f-8fa888b00e75 · outbound

This paper cites The StarCraft Multi-Agent Challenge.

Double Distillation Network for Multi-Agent Reinforcement Learning The StarCraft Multi-Agent Challenge

Reference 12

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Observation 2757e937-711f-4bd7-ad69-c80edacf0647 · outbound

This paper cites Leibo, Karl Tuyls, and Thore Grae- pel.

Double Distillation Network for Multi-Agent Reinforcement Learning Leibo, Karl Tuyls, and Thore Grae- pel

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.738488Z

Source-reported events for the cited work

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Observation a5b02059-4af0-4f9a-b961-bd9129a3dd41 · outbound

This paper cites [Tan and Motani, 2023] Chong Min John Tan and Mehul Motani.

Double Distillation Network for Multi-Agent Reinforcement Learning [Tan and Motani, 2023] Chong Min John Tan and Mehul Motani

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.729993Z

Source-reported events for the cited work

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Observation 50471655-d193-4b81-a699-2f054d02c5c1 · outbound

This paper cites Knowledge distillation and student-teacher learning for visual intelligence: A review and new outlooks.

Double Distillation Network for Multi-Agent Reinforcement Learning Knowledge distillation and student-teacher learning for visual intelligence: A review and new outlooks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.721387Z

Source-reported events for the cited work

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Observation a6ed0743-853c-437f-859a-e9b410c48b11 · outbound

This paper cites QPLEX: Duplex Dueling Multi-Agent Q-Learning.

Double Distillation Network for Multi-Agent Reinforcement Learning QPLEX: Duplex Dueling Multi-Agent Q-Learning

Reference 17

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Source-reported events for the cited work

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Observation 0b511698-04de-4d4e-9c19-e25362176728 · outbound

This paper cites Regularization-adapted anderson acceleration for multi- agent reinforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Regularization-adapted anderson acceleration for multi- agent reinforcement learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.711783Z

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.

Observation 02f6a21c-6f92-4bea-ace6-b8c716b07a55 · outbound

This paper cites En- hancing collaboration in multi-agent reinforcement learn- ing with correlated trajectories.

Double Distillation Network for Multi-Agent Reinforcement Learning En- hancing collaboration in multi-agent reinforcement learn- ing with correlated trajectories

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T05:54:06.544898Z

Source-reported events for the cited work

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Observation efd6b89f-c0be-4762-8fae-508fcdbc5254 · outbound

This paper cites Deep multiagent reinforce- ment learning: Challenges and directions.

Double Distillation Network for Multi-Agent Reinforcement Learning Deep multiagent reinforce- ment learning: Challenges and directions

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.698051Z

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.

Observation 8ddcc6d2-dcce-43ea-8014-c070bc7a4b80 · outbound

This paper cites A Survey on Knowledge Distillation of Large Language Models.

Double Distillation Network for Multi-Agent Reinforcement Learning A Survey on Knowledge Distillation of Large Language Models

Reference 21

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Source-reported events for the cited work

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Observation 2586a3b6-04be-4ae0-a96f-be108bf7cfaa · outbound

This paper cites A comprehensive survey on multi-agent rein- forcement learning for connected and automated vehicles.

Double Distillation Network for Multi-Agent Reinforcement Learning A comprehensive survey on multi-agent rein- forcement learning for connected and automated vehicles

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.687916Z

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.

Observation 6b275445-775f-4696-8925-8a90c405438f · outbound

This paper cites Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Qatten: A General Framework for Cooperative Multiagent Reinforcement Learning

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T05:54:06.556573Z

Source-reported events for the cited work

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Observation 637f0a19-6f55-459a-be36-0952e487841a · outbound

This paper cites The surprising effectiveness of ppo in cooperative multi-agent games.

Double Distillation Network for Multi-Agent Reinforcement Learning The surprising effectiveness of ppo in cooperative multi-agent games

Reference 24

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Source-reported events for the cited work

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Observation 61ddb500-7886-4255-badd-21fde4199a89 · outbound

This paper cites Unmanned aerial vehicle swarm cooperative decision-making for sead mis- sion: A hierarchical multiagent reinforcement learning ap- proach.

Double Distillation Network for Multi-Agent Reinforcement Learning Unmanned aerial vehicle swarm cooperative decision-making for sead mis- sion: A hierarchical multiagent reinforcement learning ap- proach

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.674054Z

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.

Observation a27919d6-9bef-4f0a-b71d-5001f75d1df3 · outbound

This paper cites Ctds: Centralized teacher with decentralized student for mul- tiagent reinforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Ctds: Centralized teacher with decentralized student for mul- tiagent reinforcement learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.665212Z

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.

Observation 05ad1047-7ed1-43f9-a2db-1217bd85ded3 · outbound

This paper cites Qdap: Downsizing adaptive policy for cooperative multi-agent reinforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Qdap: Downsizing adaptive policy for cooperative multi-agent reinforcement learning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-09T05:54:06.568133Z

Source-reported events for the cited work

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Observation 66fafe73-7433-4bff-830e-edc9a625f629 · outbound

This paper cites Multirobot collaborative task dynamic scheduling based on multiagent reinforcement learning with heuristic graph convolution considering robot service performance.

Double Distillation Network for Multi-Agent Reinforcement Learning Multirobot collaborative task dynamic scheduling based on multiagent reinforcement learning with heuristic graph convolution considering robot service performance

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.651425Z

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.

Observation 78f83113-7418-44f7-ad00-7baf8001470c · outbound

This paper cites Rethinking individual global max in cooperative multi- agent reinforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Rethinking individual global max in cooperative multi- agent reinforcement learning

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.787355Z

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.

Observation 0f8ea0de-e950-4414-8c5b-33cbe4911f08 · outbound

This paper cites A concise introduction to decentralized POMDPs, volume.

Double Distillation Network for Multi-Agent Reinforcement Learning A concise introduction to decentralized POMDPs, volume

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-09T05:54:06.516162Z

Source-reported events for the cited work

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Observation 565be0e4-968d-4fb5-8edf-5854024a28dc · outbound

This paper cites Ptde: Personalized training with dis- tilled execution for multi-agent reinforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Ptde: Personalized training with dis- tilled execution for multi-agent reinforcement learning

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.815173Z

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.

Observation 14790022-c54d-44db-892d-caad3236684c · outbound

This paper cites Qtran: Learn- ing to factorize with transformation for cooperative multi- agent reinforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Qtran: Learn- ing to factorize with transformation for cooperative multi- agent reinforcement learning

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-09T05:54:06.527659Z

Source-reported events for the cited work

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Observation 235ba8c1-eaa0-4f1a-b396-d1547713155e · outbound

This paper cites Policy Distillation.

Double Distillation Network for Multi-Agent Reinforcement Learning Policy Distillation

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T05:54:06.521520Z

Source-reported events for the cited work

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Observation 702019eb-c527-456e-9f4e-35afaff8472a · outbound

This paper cites Distilling the knowledge in a neural network,.

Double Distillation Network for Multi-Agent Reinforcement Learning Distilling the knowledge in a neural network,

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.796392Z

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.

Observation 5ada8b0b-73c4-4fd4-9799-87597cad877e · outbound

This paper cites Rethinking the implementation tricks and monotonicity constraint in cooperative multi-agent re- inforcement learning.

Double Distillation Network for Multi-Agent Reinforcement Learning Rethinking the implementation tricks and monotonicity constraint in cooperative multi-agent re- inforcement learning

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.778819Z

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.

Observation 79c5c1e2-f014-41c4-b1eb-e8be8436a3b9 · outbound

This paper cites [Huang et al., 2024] Anqi Huang, Yongli Wang, Xiaoliang Zhou, Haochen Zou, Xu Dong, and Xun Che.

Double Distillation Network for Multi-Agent Reinforcement Learning [Huang et al., 2024] Anqi Huang, Yongli Wang, Xiaoliang Zhou, Haochen Zou, Xu Dong, and Xun Che

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.770076Z

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.

Observation 792082a7-e14b-46e9-b124-1d85147ce2ea · outbound

This paper cites [Gou et al., 2021] Jianping Gou, Baosheng Yu, Stephen J Maybank, and Dacheng Tao.

Double Distillation Network for Multi-Agent Reinforcement Learning [Gou et al., 2021] Jianping Gou, Baosheng Yu, Stephen J Maybank, and Dacheng Tao

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:54:06.806080Z

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.

Pith citing papers

No inbound Pith citation observations are available.