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

230 papers, page 4 of 5

151. ICLR 2025On the Modeling Capabilities of Large Language Models for Sequential Decision Making
152. ICLR 2025Online Reinforcement Learning in Non-Stationary Context-Driven Environments
153. ICLR 2025Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
154. ICLR 2025Online-to-Offline RL for Agent Alignment
155. ICLR 2025Open-World Reinforcement Learning over Long Short-Term Imagination
156. ICLR 2025Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
157. ICLR 2025Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
158. ICLR 2025OptionZero: Planning with Learned Options
159. ICLR 2025ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
160. ICLR 2025Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
161. ICLR 2025PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
162. ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
163. ICLR 2025Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model
164. ICLR 2025Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy
165. ICLR 2025PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
166. ICLR 2025POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition
167. ICLR 2025Preference Elicitation for Offline Reinforcement Learning
168. ICLR 2025Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline
169. ICLR 2025Prioritized Generative Replay
170. ICLR 2025PWM: Policy Learning with Multi-Task World Models
171. ICLR 2025Q-Adapter: Customizing Pre-trained LLMs to New Preferences with Forgetting Mitigation
172. ICLR 2025Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning
173. ICLR 2025QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing
174. ICLR 2025Reconstruction-Guided Policy: Enhancing Decision-Making through Agent-Wise State Consistency
175. ICLR 2025REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments
176. ICLR 2025Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF
177. ICLR 2025Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
178. ICLR 2025Reinforcement learning with combinatorial actions for coupled restless bandits
179. ICLR 2025Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning
180. ICLR 2025Revisiting a Design Choice in Gradient Temporal Difference Learning
181. ICLR 2025REvolve: Reward Evolution with Large Language Models using Human Feedback
182. ICLR 2025Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
183. ICLR 2025Reward Learning from Multiple Feedback Types
184. ICLR 2025Risk-Sensitive Variational Actor-Critic: A Model-Based Approach
185. ICLR 2025Robust Transfer of Safety-Constrained Reinforcement Learning Agents
186. ICLR 2025RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
187. ICLR 2025Safety Representations for Safer Policy Learning
188. ICLR 2025Safety-Prioritizing Curricula for Constrained Reinforcement Learning
189. ICLR 2025Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
190. ICLR 2025Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
191. ICLR 2025Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning
192. ICLR 2025Select before Act: Spatially Decoupled Action Repetition for Continuous Control
193. ICLR 2025SELF-EVOLVED REWARD LEARNING FOR LLMS
194. ICLR 2025Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
195. ICLR 2025SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation
196. ICLR 2025SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
197. ICLR 2025Simple, Good, Fast: Self-Supervised World Models Free of Baggage
198. ICLR 2025Simplifying Deep Temporal Difference Learning
199. ICLR 2025SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback
200. ICLR 2025Solving New Tasks by Adapting Internet Video Knowledge

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.