cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending | Paper Citation Record

Observation 8bce8743-5f04-42db-95b9-04588e09b9ee · outbound

This paper cites Curriculum learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Curriculum learning

Reference 1

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Observation e8321533-fd03-4df0-bfb9-33e9d65ff7d5 · outbound

This paper cites Geometric and Physical Quantities Improve E(3) Equivariant Message Passing.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 2

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Observation c1b6fea4-b81a-4619-b744-8028bc3b6d95 · outbound

This paper cites OpenAI Gym.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending OpenAI Gym

Reference 3

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Observation 17a2bfc7-54a6-4f7d-8697-430d7a63705b · outbound

This paper cites Robust multi-agent reinforcement learning via adversarial regularization: Theoretical foundation and stable algorithms.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Robust multi-agent reinforcement learning via adversarial regularization: Theoretical foundation and stable algorithms

Reference 4

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Observation d0c64a76-72e8-42d2-9637-a02c9982c1e7 · outbound

This paper cites ${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending ${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:49:54.267260Z

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Observation cde270a0-30ce-48f5-bd85-386f816d068b · outbound

This paper cites Multi-agent deep reinforcement learning for large-scale traffic signal control.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Multi-agent deep reinforcement learning for large-scale traffic signal control

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.767000Z

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Observation 2186f324-68e7-4659-8cf1-578be6099af8 · outbound

This paper cites Prompt to transfer: Sim-to-real transfer for traffic signal control with prompt learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Prompt to transfer: Sim-to-real transfer for traffic signal control with prompt learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.751888Z

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Observation 6553f578-418f-4acb-ae10-16c3f6421f03 · outbound

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

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?

Reference 8

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Observation 60369e7c-564e-4c20-a86c-55061c991f64 · outbound

This paper cites Goal-gan: Multimodal trajectory prediction based on goal position estimation.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Goal-gan: Multimodal trajectory prediction based on goal position estimation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.737091Z

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Observation 7ed375d2-6ef5-4d1c-862b-681b0035100f · outbound

This paper cites A Survey on In-context Learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending A Survey on In-context Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.136104Z

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Observation 6b9f8659-1f60-4612-b8e0-513f6409bdb5 · outbound

This paper cites J., Li, J., Paduraru, C., Gowal, S., and Hester, T.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending J., Li, J., Paduraru, C., Gowal, S., and Hester, T

Reference 11

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Observation 5595a402-99e8-4094-aff1-a33f843483ac · outbound

This paper cites Self-paced context evaluation for contextual reinforcement learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Self-paced context evaluation for contextual reinforcement learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.721532Z

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Observation 2a3aefb0-cce6-4477-a7fc-9a7d8c9b3151 · outbound

This paper cites On the convergence theory of debiased model-agnostic meta-reinforcement learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending On the convergence theory of debiased model-agnostic meta-reinforcement learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.707397Z

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Observation ef87b529-fde0-446c-8bff-6dcc433dfdb5 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Model-agnostic meta-learning for fast adaptation of deep networks

Reference 14

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Observation b739b558-5062-441c-970d-846fe12274eb · outbound

This paper cites Automatic goal generation for reinforcement learning agents.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Automatic goal generation for reinforcement learning agents

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.682857Z

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Observation 3c292955-ea99-439a-95b3-0c2b5149435a · outbound

This paper cites Contextual Markov Decision Processes.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Contextual Markov Decision Processes

Reference 16

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Observation deaa23e6-2cb5-4d47-91b8-93bfde568955 · outbound

This paper cites Meta-Learning in Games.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Meta-Learning in Games

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:49:54.195297Z

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Observation e638e57e-0d6b-4ec6-8cba-91cb9e690c44 · outbound

This paper cites Robust Multi-Agent Reinforcement Learning with State Uncertainty.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Robust Multi-Agent Reinforcement Learning with State Uncertainty

Reference 18

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Observation a5bf4872-b2a7-40e8-901e-7c00e8d39c39 · outbound

This paper cites IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning

Reference 19

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Observation 4442ed75-4efe-4671-b296-3905f42d162b · outbound

This paper cites Prioritized level replay.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Prioritized level replay

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.668488Z

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Observation f55d1d7c-b757-41a1-a332-1b7e6b8bef4e · outbound

This paper cites Multi-Agent Reinforcement Learning for Traffic Signal Control through Universal Communication Method.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Multi-Agent Reinforcement Learning for Traffic Signal Control through Universal Communication Method

Reference 21

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Observation 17769e9d-0829-451a-b62b-d15618f65e22 · outbound

This paper cites R., and Pajarinen, J.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending R., and Pajarinen, J

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.653654Z

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Observation 99e073d4-6fd6-4048-9da1-a10a19d9218d · outbound

This paper cites Google research football: A novel reinforcement learning environment.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Google research football: A novel reinforcement learning environment

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.220946Z

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Observation 66e4915a-862f-4ff8-8f9d-ed3f2dbf24f5 · outbound

This paper cites H., Gonzalez, J.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending H., Gonzalez, J

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.226915Z

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Observation 33a56a9d-64a9-4cd5-b44b-ec8be114c5e8 · outbound

This paper cites Awq: Activation-aware weight quantization for on-device llm compression and acceleration.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Awq: Activation-aware weight quantization for on-device llm compression and acceleration

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.629125Z

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Observation 8e08bafc-809b-487c-aea5-ab698128cc62 · outbound

This paper cites Multi-agent deep reinforcement learning for multi-echelon inventory management.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Multi-agent deep reinforcement learning for multi-echelon inventory management

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.613773Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4fe8a5e0-4b85-4b5c-a89d-ebfe4e2debf0 · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.245926Z

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Observation 243501db-e2fb-448f-b141-5eda65845c25 · outbound

This paper cites DrEureka: Language Model Guided Sim-To-Real Transfer.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending DrEureka: Language Model Guided Sim-To-Real Transfer

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.251513Z

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Observation 6373eaf7-8f25-4928-b12f-5d97e4d0ec8d · outbound

This paper cites Multi-agent meta-reinforcement learning: Sharper convergence rates with task similarity.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Multi-agent meta-reinforcement learning: Sharper convergence rates with task similarity

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.598366Z

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Observation 3860828f-80fe-4207-b27e-97445fec5a25 · outbound

This paper cites Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:49:54.095788Z

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Observation 52cb87fa-97b4-4512-9f42-003ae8575670 · outbound

This paper cites PEnGUiN: Partially Equivariant Graph NeUral Networks for Sample Efficient MARL.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending PEnGUiN: Partially Equivariant Graph NeUral Networks for Sample Efficient MARL

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:49:54.070069Z

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Observation 2d0752e8-3812-416a-b471-c9b6b9b226a4 · outbound

This paper cites A., and Mowbray, M.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending A., and Mowbray, M

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.580550Z

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Observation d25d5f15-0119-478e-9497-d3d7867b3d65 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending On First-Order Meta-Learning Algorithms

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.280725Z

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Observation d76f10dd-64d4-4753-840b-ba8f3717fa7f · outbound

This paper cites Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.286553Z

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Observation 14d1d631-e50b-4d31-9bb5-c5de9b3f33db · outbound

This paper cites Evolving Curricula with Regret-Based Environment Design.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Evolving Curricula with Regret-Based Environment Design

Reference 35

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Observation ece27638-2542-4c76-a893-c7c036d872ca · outbound

This paper cites Teacher algorithms for curriculum learning of deep rl in continuously parameterized environments.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Teacher algorithms for curriculum learning of deep rl in continuously parameterized environments

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.565076Z

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Observation 3c993876-5d60-4289-a74a-7c76678fc352 · outbound

This paper cites The StarCraft Multi-Agent Challenge.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending The StarCraft Multi-Agent Challenge

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.303698Z

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Observation bbc954b2-fbe0-449b-9b59-5a4f01043f38 · outbound

This paper cites A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending A Constrained Multi-Agent Reinforcement Learning Approach to Autonomous Traffic Signal Control

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:49:53.987688Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2e950c51-3702-42c3-bd11-c43feb13a3a4 · outbound

This paper cites G., Hoogeboom, E., and Welling, M.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending G., Hoogeboom, E., and Welling, M

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.550100Z

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Observation 1d333b3d-90ef-4217-b17d-bc03d7ab2cf3 · outbound

This paper cites Learn to follow: Decentralized lifelong multi-agent pathfinding via planning and learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Learn to follow: Decentralized lifelong multi-agent pathfinding via planning and learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.535459Z

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Observation 69b1c2fc-6cc0-4e9c-bf22-60873c0177cd · outbound

This paper cites H., Wu, J., Washington, C., Sadler, B.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending H., Wu, J., Washington, C., Sadler, B

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.519724Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2a600fc5-1a07-4ffc-a446-80978cd35340 · outbound

This paper cites Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Intrinsic Motivation and Automatic Curricula via Asymmetric Self-Play

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.331348Z

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Observation b8cc58f3-6e8b-40f2-9741-7afde705b34e · outbound

This paper cites Qwen2.5: A party of foundation models, September 2024.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Qwen2.5: A party of foundation models, September 2024

Reference 43

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Observation a8f0b07b-b38b-4243-9aa6-93ece1282d61 · outbound

This paper cites Domain randomization for transferring deep neural networks from simulation to the real world.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Domain randomization for transferring deep neural networks from simulation to the real world

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.495009Z

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Observation 1a04ae97-f2a5-4ed5-a414-3e4d61a59840 · outbound

This paper cites Adapting deep visuomotor representations with weak pairwise constraints.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Adapting deep visuomotor representations with weak pairwise constraints

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.480278Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0120d4fc-5953-418c-8add-10e5d4b5cb3a · outbound

This paper cites Presslight: Learning max pressure control to coordinate traffic signals in arterial network.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Presslight: Learning max pressure control to coordinate traffic signals in arterial network

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.355477Z

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Observation d6c76b24-d557-4085-af4a-03cc43905d94 · outbound

This paper cites Colight: Learning network-level cooperation for traffic signal control.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Colight: Learning network-level cooperation for traffic signal control

Reference 47

Resolution: metadata mismatch; raw_fallback, observed 2026-08-05T14:49:53.887301Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 59ab2662-e97a-4f3a-be63-78dfe53d29c0 · outbound

This paper cites H., Peng, H., and Zhang, S.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending H., Peng, H., and Zhang, S

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.463977Z

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Observation 7594c0cf-4664-46fe-b3ed-bbe6443f7bd1 · outbound

This paper cites LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.373380Z

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Observation 5d242e2c-5998-4a57-bbba-cb96f7fa8058 · outbound

This paper cites MalLight: Influence-Aware Coordinated Traffic Signal Control for Traffic Signal Malfunctions.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending MalLight: Influence-Aware Coordinated Traffic Signal Control for Traffic Signal Malfunctions

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-05T14:49:53.774193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 29b6a978-c4e8-4209-a457-3a69175d1852 · outbound

This paper cites Webshop: Towards scalable real-world web interaction with grounded language agents.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Webshop: Towards scalable real-world web interaction with grounded language agents

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.449480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 53c43ccb-bf17-41f5-9be0-bc94893204e4 · outbound

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

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending The surprising effectiveness of ppo in cooperative multi-agent games

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.397210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0527413-2068-46f6-847a-58ab26c5a296 · outbound

This paper cites EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending EnvGen: Generating and Adapting Environments via LLMs for Training Embodied Agents

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.402378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9690a80-875f-460a-b9b6-f89d8d81074e · outbound

This paper cites Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Cityflow: A multi-agent reinforcement learning environment for large scale city traffic scenario

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.426021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fbc0c12f-0092-48db-84ac-524b0e2b01ca · outbound

This paper cites Robust multi-agent reinforcement learning with model uncertainty.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Robust multi-agent reinforcement learning with model uncertainty

Reference 55

Resolution: verified exact; raw_fallback, observed 2026-08-05T14:49:53.736368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7955efdf-ec44-40fa-914e-0058d2a25487 · outbound

This paper cites No-regret learning in time-varying zero-sum games.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending No-regret learning in time-varying zero-sum games

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.410813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2761b115-2637-4c60-9cae-c93b17fedbc7 · outbound

This paper cites Learning meta representations for agents in multi-agent reinforcement learning.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Learning meta representations for agents in multi-agent reinforcement learning

Reference 57

Resolution: verified exact; raw_fallback, observed 2026-08-05T14:49:53.660591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9455f57b-0e5d-48fe-b1f0-654d389f2d71 · outbound

This paper cites Met-mapf: A metamorphic testing approach for multi-agent path finding algorithms.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Met-mapf: A metamorphic testing approach for multi-agent path finding algorithms

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T14:49:54.395671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a3522728-cdb9-4801-b7fa-c7da52b77948 · outbound

This paper cites P., and Westerlund, T.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending P., and Westerlund, T

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.440473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b34fbfef-bfd4-465c-9c65-413ffe6c4bdd · outbound

This paper cites write newline.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending write newline

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T14:49:53.446298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers