Multi-Agent RL papers, 2023–2026

Key findings

• Multi-Agent RL went from 311 papers in 2023 to 868 in 2026, roughly 2.8x in three years.
• NeurIPS publishes the most Multi-Agent RL work: 809 papers from 2023 to 2026, 38% of the four-venue total.
• The fastest-growing overlap is with Multimodal LLMs: papers tagged with both rose from 9 in 2023 to 70 in 2026.
• Among the 5 topics under Games and Planning, it ranks #1 by 2026 paper count; the fastest grower in the group, Classical Planning, is up 3.3x versus 2.8x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 20262-Step Agent: How a Bayesian Decision Maker Learns from AI-Decision Support
• ICML 2026A Causal Decomposition Approach for Fair Contextual Multi-Armed Bandits
• ICLR 2026Calibrated Information Bottleneck for Trusted Multi-modal Clustering
• CVPR 2026A Sanity Check for Multi-In-Domain Face Forgery Detection in the
• NeurIPS 2025Algorithms and SQ Lower Bounds for Robustly Learning Real-valued Multi-Index Models
• ICML 2025A Classification View on Meta Learning Bandits
• ICLR 2025BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts
• CVPR 2025All-Day Multi-Camera Multi-Target Tracking
• NeurIPS 2024A New Multi-Source Light Detection Benchmark and Semi-Supervised Focal Light Detection
• ICML 2024A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization
• ICLR 2024An Intuitive Multi-Frequency Feature Representation for SO(3)-Equivariant Networks
• CVPR 2024DeconfuseTrack: Dealing with Confusion for Multi-Object Tracking
• NeurIPS 2023A Novel Approach for Effective Multi-View Clustering with Information-Theoretic Perspective
• ICML 2023A Framework for Adapting Offline Algorithms to Solve Combinatorial Multi-Armed Bandit Problems with Bandit Feedback
• ICLR 2023An Additive Instance-Wise Approach to Multi-class Model Interpretation
• CVPR 2023A Light Touch Approach to Teaching Transformers Multi-View Geometry
• NeurIPS 2026A Black-Box Reduction from Regret to Multi-Level Coverage
• ICML 2026A Consensus Anchor-guided Hypergraph Framework for Incomplete Multi-view Clustering
• ICLR 2026Confident Block Diagonal Structure-Aware Invariable Graph Completion for Incomplete Multi-view Clustering
• CVPR 2026Anti-Degradation Lifelong Multi-View Clustering

All Multi-Agent RL papers

319 papers, page 3 of 7

101. NeurIPS 2026Finite-Sample Convergence in Networked Average Reward MARL: Decentralization Pitfalls and Entropy Remedies
102. NeurIPS 2026FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration
103. NeurIPS 2026FlashFFN: Multi-Head Decomposition Enables I/O-Aware Feed-Forward Network
104. NeurIPS 2026FlowLeak: Coverage-Guided Extraction of Dynamic Workflows in LLM-Based Multi-Agent Systems
105. NeurIPS 2026FlowSteer: Prompt-Only Workflow Steering Exposes Planning-Time Vulnerabilities in Multi-Agent LLM Systems
106. NeurIPS 2026FML-bench: A Controlled Study of AI Research Agent Strategies from the Perspective of Search Dynamics
107. NeurIPS 2026Focusing Influence Mechanism for Multi-Agent Reinforcement Learning
108. NeurIPS 2026Found in Conversation: LLMs Teach Themselves to Close the Multi-Turn Gap
109. NeurIPS 2026Frequency-Structured Hamiltonian Neural Network for Multi-Timescale Dynamics
110. NeurIPS 2026From Chats to Markets: AgenticPay for LLM-Powered Negotiation in Multi-Agent Commerce
111. NeurIPS 2026From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills
112. NeurIPS 2026From Talking Words to Sharing Thoughts: Scalable Multi-LLM Aggregation via Structured Message Passing
113. NeurIPS 2026Generalized Intention Modeling in Multi-Agent Reinforcement Learning
114. NeurIPS 2026Grounding Agent Reasoning with Structured Process Supervision for Multi-turn Reinforcement Learning
115. NeurIPS 2026Group of Skills: Group-Structured Skill Retrieval for Agent Skill Libraries
116. NeurIPS 2026Group Perspective Matters: Regulating Debate Relationships Can Mitigate Blind Conformity in Multi-Agent Debate
117. NeurIPS 2026GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations
118. NeurIPS 2026HAI: Hierarchical Anchored Interaction for Multi-View Bimanual World Models
119. NeurIPS 2026Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting
120. NeurIPS 2026Heterogeneous Agent Collaborative Reinforcement Learning
121. NeurIPS 2026How LLMs Distinguish Threats from Offers
122. NeurIPS 2026How to Interpret Agent Behavior
123. NeurIPS 2026HyperSkill: Multi-Modal Skill Learning on the Unit Hypersphere
124. NeurIPS 2026Implicit Value Probing: Inferring Human Value Preferences via Strategic Multi-Turn Conversations
125. NeurIPS 2026Improved Sample Complexity for Markov Games via Variance-Aware Bandit Learning
126. NeurIPS 2026Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics
127. NeurIPS 2026Individuals Matter: Improving Deep Multi-View Clustering via Explicit Single-View Enhancement
128. NeurIPS 2026InfoFlow: A Framework for Multi-Layer Transformer Analysis
129. NeurIPS 2026Integrating Strengths of Different Multi-Agent Workflows via Step-Aware Hybrid Topology Planning
130. NeurIPS 2026Inter-Agent Influence: Evaluating Persuasion, Deception and Coercion in Multi-Agent Systems
131. NeurIPS 2026Is Your LLM-as-a-Recommender Agent Trustable? LLMs' Recommendation is Easily Hacked by Biases (Preferences)
132. NeurIPS 2026Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs
133. NeurIPS 2026Jacobian Descent for Multi-Objective Optimization
134. NeurIPS 2026Know Your Task, Learn It Right: Task-Aware Optimistic Value Learning for Multi-Task Multi-Agent Reinforcement Learning
135. NeurIPS 2026KV-PRM: Efficient Process Reward Modeling via KV-Cache Transfer for Multi-Agent Test-Time Scaling
136. NeurIPS 2026Language-Based Agent Control
137. NeurIPS 2026LDPCache: Locally Differentially Private Multi-Query Processing with Cache Optimization for Large Language Models
138. NeurIPS 2026Learning in Causal Markov Games
139. NeurIPS 2026Learning Large-Scale Competitive Team Behaviors with Mean-Field Interactions
140. NeurIPS 2026Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry
141. NeurIPS 2026Learning When to Collaborate: Selective Multi-Agent Medical Reasoning via Uncertainty-Aware Routing
142. NeurIPS 2026LLM-Based Multi-Agent Blackboard System for Information Discovery in Data Science
143. NeurIPS 2026LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models
144. NeurIPS 2026LongMINT: Evaluating Memory under Multi-Target Interference in Long-Horizon Agent Systems
145. NeurIPS 2026LoRASpace: A Pool-Wide Shared Substrate for Static and Dynamic Multi-LoRA Composition
146. NeurIPS 2026MACRO: Training-free Multi-plane Attention for Closeup Render Optimization
147. NeurIPS 2026MAGE: Towards Generalizable Multi-timescale EEG Representations
148. NeurIPS 2026MANGO:Multi-Angle Neural Gated Operators for Chirp-Perturbed PDEs
149. NeurIPS 2026MARBLE: an Agent Benchmark for Spatial Reasoning and Visual Abstraction
150. NeurIPS 2026MaRiO: Multi-agent Collaborative Reasoning via Shared Observations in MLLMs

FAQ

How many Multi-Agent RL papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,126 in total: 311 in 2023, 373 in 2024, 574 in 2025, 868 in 2026.

How many Multi-Agent RL papers are at NeurIPS 2026?

NeurIPS 2026 has 319 Multi-Agent RL papers, versus 255 the year before.

How many Multi-Agent RL papers are at ICLR 2026?

ICLR 2026 has 153 Multi-Agent RL papers, versus 91 the year before.

How many Multi-Agent RL papers are at ICML 2026?

ICML 2026 has 224 Multi-Agent RL papers, versus 115 the year before.

How many Multi-Agent RL papers are at CVPR 2026?

CVPR 2026 has 172 Multi-Agent RL papers, versus 113 the year before.

Which conference publishes the most Multi-Agent RL papers?

NeurIPS, with 809 papers from 2023 to 2026.