Reinforcement Learning papers, 2023–2026

Key findings

• Reinforcement Learning went from 1,070 papers in 2023 to 2,985 in 2026, roughly 2.8x in three years.
• NeurIPS publishes the most Reinforcement Learning work: 2,494 papers from 2023 to 2026, 36% of the four-venue total.
• The fastest-growing overlap is with Reasoning Models: papers tagged with both rose from 9 in 2023 to 437 in 2026.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026\texttt{FEROM}: Frontier Endogenous Reveal-Order Marginal Policy Optimization for Masked Diffusion LMs
• ICML 2026$\text{DT}^\text{2}$: Decision-Targeted Digital Twins
• ICLR 2026$\nabla$-Reasoner: LLM Reasoning via Test-Time Gradient Descent in Textual Space
• CVPR 2026A Causal Marriage between VLM and IRM from Understanding to
• NeurIPS 2025$\texttt{G1}$: Teaching LLMs to Reason on Graphs with Reinforcement Learning
• ICML 2025A Computationally Efficient Algorithm for Infinite-Horizon Average-Reward Linear MDPs
• ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
• CVPR 2025All-Optical Nonlinear Diffractive Deep Network for Ultrafast Image Denoising
• NeurIPS 2024A Critical Evaluation of AI Feedback for Aligning Large Language Models
• ICML 2024${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
• ICLR 2024A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
• CVPR 2024DMR: Decomposed Multi-Modality Representations for Frames and Events Fusion in Visual Reinforcement Learning
• NeurIPS 2023“Why Not Looking backward?” A Robust Two-Step Method to Automatically Terminate Bayesian Optimization
• ICML 2023A Connection between One-Step RL and Critic Regularization in Reinforcement Learning
• ICLR 2023$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games
• CVPR 2023"Seeing" Electric Network Frequency From Events
• NeurIPS 2026$\varphi$TD: Distributional Reinforcement Learning using Characteristic Functions
• ICML 2026$\textit{S}$-SPPO: Semantic-Calibrated Self-Play Preference Optimization
• ICLR 2026$AutoDrive\text{-}P^3$: Unified Chain of Perception–Prediction–Planning Thought via Reinforcement Fine-Tuning
• CVPR 2026AdaptVision Efficient Vision-Language Models via Adaptive Visual Acquisition

All Reinforcement Learning papers

1,190 papers, page 20 of 24

951. NeurIPS 2024Learning to Discuss Strategically: A Case Study on One Night Ultimate Werewolf
952. NeurIPS 2024Learning Versatile Skills with Curriculum Masking
953. NeurIPS 2024Learning World Models for Unconstrained Goal Navigation
954. NeurIPS 2024LeDex: Training LLMs to Better Self-Debug and Explain Code
955. NeurIPS 2024Leveraging Separated World Model for Exploration in Visually Distracted Environments
956. NeurIPS 2024LLM-based Skill Diffusion for Zero-shot Policy Adaptation
957. NeurIPS 2024Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs
958. NeurIPS 2024Logarithmic Smoothing for Pessimistic Off-Policy Evaluation, Selection and Learning
959. NeurIPS 2024MADiff: Offline Multi-agent Learning with Diffusion Models
960. NeurIPS 2024Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion
961. NeurIPS 2024Making Offline RL Online: Collaborative World Models for Offline Visual Reinforcement Learning
962. NeurIPS 2024Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
963. NeurIPS 2024Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
964. NeurIPS 2024Measuring Goal-Directedness
965. NeurIPS 2024Measuring Mutual Policy Divergence for Multi-Agent Sequential Exploration
966. NeurIPS 2024Melting Pot Contest: Charting the Future of Generalized Cooperative Intelligence
967. NeurIPS 2024MeMo: Meaningful, Modular Controllers via Noise Injection
968. NeurIPS 2024Meta-Controller: Few-Shot Imitation of Unseen Embodiments and Tasks in Continuous Control
969. NeurIPS 2024Meta-DT: Offline Meta-RL as Conditional Sequence Modeling with World Model Disentanglement
970. NeurIPS 2024Meta-Reinforcement Learning with Universal Policy Adaptation: Provable Near-Optimality under All-task Optimum Comparator
971. NeurIPS 2024MetaCURL: Non-stationary Concave Utility Reinforcement Learning
972. NeurIPS 2024Mimicking To Dominate: Imitation Learning Strategies for Success in Multiagent Games
973. NeurIPS 2024Minimax Optimal and Computationally Efficient Algorithms for Distributionally Robust Offline Reinforcement Learning
974. NeurIPS 2024Minimum Entropy Coupling with Bottleneck
975. NeurIPS 2024MiSO: Optimizing brain stimulation to create neural activity states
976. NeurIPS 2024Mitigating Covariate Shift in Behavioral Cloning via Robust Stationary Distribution Correction
977. NeurIPS 2024Mitigating Partial Observability in Sequential Decision Processes via the Lambda Discrepancy
978. NeurIPS 2024Mitigating Reward Overoptimization via Lightweight Uncertainty Estimation
979. NeurIPS 2024Model-based Diffusion for Trajectory Optimization
980. NeurIPS 2024Model-Based Transfer Learning for Contextual Reinforcement Learning
981. NeurIPS 2024Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation
982. NeurIPS 2024MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
983. NeurIPS 2024Multi-Agent Coordination via Multi-Level Communication
984. NeurIPS 2024Multi-Agent Domain Calibration with a Handful of Offline Data
985. NeurIPS 2024Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
986. NeurIPS 2024Multi-Reward Best Policy Identification
987. NeurIPS 2024Multi-turn Reinforcement Learning with Preference Human Feedback
988. NeurIPS 2024Multimodal Large Language Models Make Text-to-Image Generative Models Align Better
989. NeurIPS 2024Mutli-Armed Bandits with Network Interference
990. NeurIPS 2024N-agent Ad Hoc Teamwork
991. NeurIPS 2024Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model
992. NeurIPS 2024Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms
993. NeurIPS 2024Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs
994. NeurIPS 2024NeoRL: Efficient Exploration for Nonepisodic RL
995. NeurIPS 2024NetworkGym: Reinforcement Learning Environments for Multi-Access Traffic Management in Network Simulation
996. NeurIPS 2024Neural Combinatorial Optimization for Robust Routing Problem with Uncertain Travel Times
997. NeurIPS 2024NeuralPlane: An Efficiently Parallelizable Platform for Fixed-wing Aircraft Control with Reinforcement Learning
998. NeurIPS 2024No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery
999. NeurIPS 2024No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO
1000. NeurIPS 2024Noise Contrastive Alignment of Language Models with Explicit Rewards

FAQ

How many Reinforcement Learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

6,885 in total: 1,070 in 2023, 1,190 in 2024, 1,640 in 2025, 2,985 in 2026.

How many Reinforcement Learning papers are at NeurIPS 2026?

NeurIPS 2026 has 760 Reinforcement Learning papers, versus 784 the year before.

How many Reinforcement Learning papers are at ICLR 2026?

ICLR 2026 has 911 Reinforcement Learning papers, versus 379 the year before.

How many Reinforcement Learning papers are at ICML 2026?

ICML 2026 has 1,021 Reinforcement Learning papers, versus 405 the year before.

How many Reinforcement Learning papers are at CVPR 2026?

CVPR 2026 has 293 Reinforcement Learning papers, versus 72 the year before.

Which conference publishes the most Reinforcement Learning papers?

NeurIPS, with 2,494 papers from 2023 to 2026.