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

338 papers, page 3 of 7

101. ICML 2026The Role of Target Update Frequencies in Q-Learning
102. ICML 2026The Surprising Difficulty of Search in Model-Based Reinforcement Learning
103. ICML 2026TQL: Scaling Q-Functions with Transformers by Preventing Attention Collapse
104. ICML 2026TraCeS: Learning Per-Timestep Constraint-Violation Credit from Sparse Trajectory-Level Labels
105. ICML 2026Trajectory-Level Data Augmentation for Offline Reinforcement Learning
106. ICML 2026Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
107. ICML 2026Trust Region Masking for Long-Horizon LLM Reinforcement Learning
108. ICML 2026TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
109. ICML 2026Video-Based Optimal Transport for Feedback-Efficient Offline Preference-Based Reinforcement Learning
110. ICML 2026VideoSEG-O3: A Multi-turn Reinforcement Learning Framework for Reasoning Video Object Segmentation
111. ICML 2026VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning
112. ICML 2026What Makes Value Learning Efficient in Residual Reinforcement Learning?
113. ICML 2026Why Linear Recurrent Memory Works in Partially Observable Reinforcement Learning
114. ICML 2025A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
115. ICML 2025A Reductions Approach to Risk-Sensitive Reinforcement Learning with Optimized Certainty Equivalents
116. ICML 2025A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
117. ICML 2025Accelerating Quantum Reinforcement Learning with a Quantum Natural Policy Gradient Based Approach
118. ICML 2025Action-Dependent Optimality-Preserving Reward Shaping
119. ICML 2025Activation by Interval-wise Dropout: A Simple Way to Prevent Neural Networks from Plasticity Loss
120. ICML 2025Actor-Critics Can Achieve Optimal Sample Efficiency
121. ICML 2025Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
122. ICML 2025An Optimistic Algorithm for online CMDPS with Anytime Adversarial Constraints
123. ICML 2025Automatic Reward Shaping from Confounded Offline Data
124. ICML 2025Behavior-agnostic Task Inference for Robust Offline In-context Reinforcement Learning
125. ICML 2025Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
126. ICML 2025Benchmarking Quantum Reinforcement Learning
127. ICML 2025Beyond Bradley-Terry Models: A General Preference Model for Language Model Alignment
128. ICML 2025Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning
129. ICML 2025Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PC
130. ICML 2025C2IQL: Constraint-Conditioned Implicit Q-learning for Safe Offline Reinforcement Learning
131. ICML 2025CLARIFY: Contrastive Preference Reinforcement Learning for Untangling Ambiguous Queries
132. ICML 2025Combinatorial Reinforcement Learning with Preference Feedback
133. ICML 2025Conservative Offline Goal-Conditioned Implicit V-Learning
134. ICML 2025Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium
135. ICML 2025Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
136. ICML 2025DIME: Diffusion-Based Maximum Entropy Reinforcement Learning
137. ICML 2025Directly Forecasting Belief for Reinforcement Learning with Delays
138. ICML 2025Distributionally Robust Policy Learning under Concept Drifts
139. ICML 2025Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
140. ICML 2025Empirical Design in Reinforcement Learning
141. ICML 2025Flow Q-Learning
142. ICML 2025Gradient Boosting Reinforcement Learning
143. ICML 2025Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning
144. ICML 2025Hierarchical Reinforcement Learning with Targeted Causal Interventions
145. ICML 2025Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals
146. ICML 2025Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning
147. ICML 2025Hyperspherical Normalization for Scalable Deep Reinforcement Learning
148. ICML 2025IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
149. ICML 2025Improving Transformer World Models for Data-Efficient RL
150. ICML 2025In-Context Reinforcement Learning From Suboptimal Historical Data

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.