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

575 papers, page 5 of 12

201. ICLR 2026Octax: Accelerated CHIP-8 Arcade Environments for Reinforcement Learning in JAX
202. ICLR 2026Off-Policy Evaluation for Ranking Policies under Deterministic Logging Policies
203. ICLR 2026Off-Policy Safe Reinforcement Learning with Cost-Constrained Optimistic Exploration
204. ICLR 2026Offline Preference-Based Value Optimization
205. ICLR 2026Offline Reinforcement Learning with Adaptive Feature Fusion
206. ICLR 2026On Discovering Algorithms for Adversarial Imitation Learning
207. ICLR 2026On Entropy Control in LLM-RL Algorithms
208. ICLR 2026On the Computational Limits of AI4S-RL : A Unified $\varepsilon$-$N$ Analysis
209. ICLR 2026On the Design of KL-Regularized Policy Gradient Algorithms for LLM Reasoning
210. ICLR 2026On the Direction of RLVR Updates for LLM Reasoning: Identification and Exploitation
211. ICLR 2026On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification
212. ICLR 2026On the Tension Between Optimality and Adversarial Robustness in Policy Optimization
213. ICLR 2026One Model for All Tasks: Leveraging Efficient World Models in Multi-Task Planning
214. ICLR 2026One-Step Flow Q-Learning: Addressing the Diffusion Policy Bottleneck in Offline Reinforcement Learning
215. ICLR 2026OPPO: Accelerating PPO-based RLHF via Pipeline Overlap
216. ICLR 2026OPRIDE: Efficient Offline Preference-based Reinforcement Learning via In-Dataset Exploration
217. ICLR 2026Optimal Robust Subsidy Policies for Irrational Agent in Principal-Agent MDPs
218. ICLR 2026Optimistic Task Inference for Behavior Foundation Models
219. ICLR 2026Parameter-Efficient Reinforcement Learning using Prefix Optimization
220. ICLR 2026Partially Equivariant Reinforcement Learning in Symmetry-Breaking Environments
221. ICLR 2026Peak-Return Greedy Slicing: Subtrajectory Selection for Transformer-based Offline RL
222. ICLR 2026Peng's Q($\lambda$) for Conservative Value Estimation in Offline Reinforcement Learning
223. ICLR 2026Policy Likelihood-based Query Sampling and Critic-Exploited Reset for Efficient Preference-based Reinforcement Learning
224. ICLR 2026Policy Newton Algorithm in Reproducing Kernel Hilbert Space
225. ICLR 2026PolicyFlow: Policy Optimization with Continuous Normalizing Flow in Reinforcement Learning
226. ICLR 2026Polychromic Objectives for Reinforcement Learning
227. ICLR 2026Post-training Large Language Models for Diverse High-Quality Responses
228. ICLR 2026Potentially Optimal Joint Actions Recognition for Cooperative Multi-Agent Reinforcement Learning
229. ICLR 2026Predictive CVaR Q-learning
230. ICLR 2026Preference-based Policy Optimization from Sparse-reward Offline Dataset
231. ICLR 2026Primal-Dual Policy Optimization for Adversarial Linear CMDPs
232. ICLR 2026Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning
233. ICLR 2026Probing in the Dark: State Entropy Maximization for POMDPs
234. ICLR 2026Probing to Refine: Reinforcement Distillation of LLM Reasoners via Explanatory Inversion
235. ICLR 2026Prompt Curriculum Learning for Efficient LLM Post-Training
236. ICLR 2026Q-Learning with Adjoint Matching
237. ICLR 2026Q-Learning with Fine-Grained Gap-Dependent Regret
238. ICLR 2026Q-learning with Posterior Sampling
239. ICLR 2026Q-RAG: Long Context Multi‑Step Retrieval via Value‑Based Embedder Training
240. ICLR 2026Quantile Advantage Estimation for Entropy-Safe Reasoning
241. ICLR 2026Queue Length Regret Bounds for Contextual Queueing Bandits
242. ICLR 2026R2-Dreamer: Redundancy-Reduced World Models without Decoders or Augmentation
243. ICLR 2026RD-HRL: Generating Reliable Sub-Goals for Long-Horizon Sparse-Reward Tasks
244. ICLR 2026REA-RL: Reflection-Aware Online Reinforcement Learning for Efficient Reasoning
245. ICLR 2026Reasoning as Representation: Rethinking Visual Reinforcement Learning in Image Quality Assessment
246. ICLR 2026Recurrent Action Transformer with Memory
247. ICLR 2026Reevaluating Policy Gradient Methods for Imperfect-Information Games
248. ICLR 2026Reference Guided Skill Discovery
249. ICLR 2026Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLM
250. ICLR 2026ReFORM: Reflected Flows for On-support Offline RL via Noise Manipulation

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.