General ML · reinforcement learning papers, 2023–2026

Key findings

• General ML · reinforcement learning went from 287 papers in 2023 to 575 in 2026, roughly 2.0x in three years.
• ICLR publishes the most General ML · reinforcement learning work: 847 papers from 2023 to 2026, 51% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 2 in 2023 to 34 in 2026.
• Among the 6 topics under General Machine Learning, it ranks #2 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 2.0x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
• ICML 2026De-attribute to Forget for LLM Unlearning
• ICLR 2026AbstRaL: Augmenting LLMs' Reasoning by Reinforcing Abstract Thinking
• CVPR 2026Dynamic Important Example Mining for Reinforcement Finetuning
• NeurIPS 2025RULE: Reinforcement UnLEarning Achieves Forget-retain Pareto Optimality
• ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
• ICLR 2025A General Framework for Off-Policy Learning with Partially-Observed Reward
• CVPR 2025Automated Proof of Polynomial Inequalities via Reinforcement Learning
• NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
• ICML 2024Provable Risk-Sensitive Distributional Reinforcement Learning with General Function Approximation
• ICLR 2024Bandits with Replenishable Knapsacks: the Best of both Worlds
• CVPR 2024Improving Unsupervised Hierarchical Representation with Reinforcement Learning
• NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
• ICML 2023Non-stationary Reinforcement Learning under General Function Approximation
• ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
• CVPR 2023Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
• NeurIPS 2026Learning When to Stop: Selective Imitation Learning Under Arbitrary Dynamics Shift
• ICML 2026Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning
• ICLR 2026APPLE: Toward General Active Perception via Reinforcement Learning
• CVPR 2026Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

All General ML · reinforcement learning papers

146 papers, page 3 of 3

101. NeurIPS 2023Prioritizing Samples in Reinforcement Learning with Reducible Loss
102. NeurIPS 2023Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability
103. NeurIPS 2023Provably Efficient Offline Reinforcement Learning in Regular Decision Processes
104. NeurIPS 2023Provably Robust Temporal Difference Learning for Heavy-Tailed Rewards
105. NeurIPS 2023Provably Safe Reinforcement Learning with Step-wise Violation Constraints
106. NeurIPS 2023Recovering from Out-of-sample States via Inverse Dynamics in Offline Reinforcement Learning
107. NeurIPS 2023Reduced Policy Optimization for Continuous Control with Hard Constraints
108. NeurIPS 2023Reflexion: language agents with verbal reinforcement learning
109. NeurIPS 2023Regret Minimization via Saddle Point Optimization
110. NeurIPS 2023Reinforcement Learning with Simple Sequence Priors
111. NeurIPS 2023Reinforcement-Enhanced Autoregressive Feature Transformation: Gradient-steered Search in Continuous Space for Postfix Expressions
112. NeurIPS 2023Reining Generalization in Offline Reinforcement Learning via Representation Distinction
113. NeurIPS 2023Replicability in Reinforcement Learning
114. NeurIPS 2023Replicable Reinforcement Learning
115. NeurIPS 2023Revisiting the Minimalist Approach to Offline Reinforcement Learning
116. NeurIPS 2023Reward Scale Robustness for Proximal Policy Optimization via DreamerV3 Tricks
117. NeurIPS 2023Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning
118. NeurIPS 2023Rewiring Neurons in Non-Stationary Environments
119. NeurIPS 2023RL-ViGen: A Reinforcement Learning Benchmark for Visual Generalization
120. NeurIPS 2023Safety Gymnasium: A Unified Safe Reinforcement Learning Benchmark
121. NeurIPS 2023Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning
122. NeurIPS 2023Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities
123. NeurIPS 2023Seeing is not Believing: Robust Reinforcement Learning against Spurious Correlation
124. NeurIPS 2023Self-Predictive Universal AI
125. NeurIPS 2023Sequential Preference Ranking for Efficient Reinforcement Learning from Human Feedback
126. NeurIPS 2023SMACv2: An Improved Benchmark for Cooperative Multi-Agent Reinforcement Learning
127. NeurIPS 2023Small batch deep reinforcement learning
128. NeurIPS 2023SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning
129. NeurIPS 2023State Sequences Prediction via Fourier Transform for Representation Learning
130. NeurIPS 2023StateMask: Explaining Deep Reinforcement Learning through State Mask
131. NeurIPS 2023Successor-Predecessor Intrinsic Exploration
132. NeurIPS 2023Suggesting Variable Order for Cylindrical Algebraic Decomposition via Reinforcement Learning
133. NeurIPS 2023Supported Value Regularization for Offline Reinforcement Learning
134. NeurIPS 2023Survival Instinct in Offline Reinforcement Learning
135. NeurIPS 2023Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
136. NeurIPS 2023Taylor TD-learning
137. NeurIPS 2023Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning
138. NeurIPS 2023Tempo Adaptation in Non-stationary Reinforcement Learning
139. NeurIPS 2023The Benefits of Being Distributional: Small-Loss Bounds for Reinforcement Learning
140. NeurIPS 2023The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
141. NeurIPS 2023TradeMaster: A Holistic Quantitative Trading Platform Empowered by Reinforcement Learning
142. NeurIPS 2023Train Hard, Fight Easy: Robust Meta Reinforcement Learning
143. NeurIPS 2023Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints
144. NeurIPS 2023Two Heads are Better Than One: A Simple Exploration Framework for Efficient Multi-Agent Reinforcement Learning
145. NeurIPS 2023Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
146. NeurIPS 2023When is Agnostic Reinforcement Learning Statistically Tractable?

FAQ

How many General ML · reinforcement learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,676 in total: 287 in 2023, 403 in 2024, 411 in 2025, 575 in 2026.

How many General ML · reinforcement learning papers are at NeurIPS 2026?

NeurIPS 2026 has 113 General ML · reinforcement learning papers, versus 108 the year before.

How many General ML · reinforcement learning papers are at ICLR 2026?

ICLR 2026 has 335 General ML · reinforcement learning papers, versus 230 the year before.

How many General ML · reinforcement learning papers are at ICML 2026?

ICML 2026 has 113 General ML · reinforcement learning papers, versus 71 the year before.

How many General ML · reinforcement learning papers are at CVPR 2026?

CVPR 2026 has 14 General ML · reinforcement learning papers, versus 2 the year before.

Which conference publishes the most General ML · reinforcement learning papers?

ICLR, with 847 papers from 2023 to 2026.