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

403 papers, page 4 of 9

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

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.