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

216 papers, page 4 of 5

151. ICLR 2024Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency
152. ICLR 2024Revisiting Data Augmentation in Deep Reinforcement Learning
153. ICLR 2024Revisiting Plasticity in Visual Reinforcement Learning: Data, Modules and Training Stages
154. ICLR 2024Reward Design for Justifiable Sequential Decision-Making
155. ICLR 2024Reward Model Ensembles Help Mitigate Overoptimization
156. ICLR 2024Reward-Consistent Dynamics Models are Strongly Generalizable for Offline Reinforcement Learning
157. ICLR 2024Reward-Free Curricula for Training Robust World Models
158. ICLR 2024RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment
159. ICLR 2024RLIF: Interactive Imitation Learning as Reinforcement Learning
160. ICLR 2024Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula
161. ICLR 2024Robust Model Based Reinforcement Learning Using $\mathcal{L}_1$ Adaptive Control
162. ICLR 2024S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
163. ICLR 2024Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
164. ICLR 2024Safe RLHF: Safe Reinforcement Learning from Human Feedback
165. ICLR 2024SafeDreamer: Safe Reinforcement Learning with World Models
166. ICLR 2024Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
167. ICLR 2024Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
168. ICLR 2024Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
169. ICLR 2024Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
170. ICLR 2024Sample-Efficient Quality-Diversity by Cooperative Coevolution
171. ICLR 2024Score Models for Offline Goal-Conditioned Reinforcement Learning
172. ICLR 2024Score Regularized Policy Optimization through Diffusion Behavior
173. ICLR 2024SEABO: A Simple Search-Based Method for Offline Imitation Learning
174. ICLR 2024Selective Visual Representations Improve Convergence and Generalization for Embodied AI
175. ICLR 2024Simple Hierarchical Planning with Diffusion
176. ICLR 2024Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
177. ICLR 2024Skill or Luck? Return Decomposition via Advantage Functions
178. ICLR 2024Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
179. ICLR 2024Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution
180. ICLR 2024Spatially-Aware Transformers for Embodied Agents
181. ICLR 2024SRL: Scaling Distributed Reinforcement Learning to Over Ten Thousand Cores
182. ICLR 2024STARC: A General Framework For Quantifying Differences Between Reward Functions
183. ICLR 2024Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets
184. ICLR 2024Submodular Reinforcement Learning
185. ICLR 2024TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
186. ICLR 2024Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
187. ICLR 2024TD-MPC2: Scalable, Robust World Models for Continuous Control
188. ICLR 2024Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
189. ICLR 2024The Curse of Diversity in Ensemble-Based Exploration
190. ICLR 2024The Effective Horizon Explains Deep RL Performance in Stochastic Environments
191. ICLR 2024The Generalization Gap in Offline Reinforcement Learning
192. ICLR 2024The Update-Equivalence Framework for Decision-Time Planning
193. ICLR 2024The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
194. ICLR 2024Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
195. ICLR 2024TorchRL: A data-driven decision-making library for PyTorch
196. ICLR 2024Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games
197. ICLR 2024Towards Imitation Learning to Branch for MIP: A Hybrid Reinforcement Learning based Sample Augmentation Approach
198. ICLR 2024Towards Offline Opponent Modeling with In-context Learning
199. ICLR 2024Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
200. ICLR 2024Towards Principled Representation Learning from Videos for Reinforcement Learning

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.