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

847 papers, page 5 of 17

201. ICLR 2026OPPO: Accelerating PPO-based RLHF via Pipeline Overlap
202. ICLR 2026OPRIDE: Efficient Offline Preference-based Reinforcement Learning via In-Dataset Exploration
203. ICLR 2026Optimal Robust Subsidy Policies for Irrational Agent in Principal-Agent MDPs
204. ICLR 2026Optimistic Task Inference for Behavior Foundation Models
205. ICLR 2026Parameter-Efficient Reinforcement Learning using Prefix Optimization
206. ICLR 2026Partially Equivariant Reinforcement Learning in Symmetry-Breaking Environments
207. ICLR 2026Peak-Return Greedy Slicing: Subtrajectory Selection for Transformer-based Offline RL
208. ICLR 2026Peng's Q($\lambda$) for Conservative Value Estimation in Offline Reinforcement Learning
209. ICLR 2026Policy Likelihood-based Query Sampling and Critic-Exploited Reset for Efficient Preference-based Reinforcement Learning
210. ICLR 2026Policy Newton Algorithm in Reproducing Kernel Hilbert Space
211. ICLR 2026PolicyFlow: Policy Optimization with Continuous Normalizing Flow in Reinforcement Learning
212. ICLR 2026Polychromic Objectives for Reinforcement Learning
213. ICLR 2026Post-training Large Language Models for Diverse High-Quality Responses
214. ICLR 2026Potentially Optimal Joint Actions Recognition for Cooperative Multi-Agent Reinforcement Learning
215. ICLR 2026Predictive CVaR Q-learning
216. ICLR 2026Preference-based Policy Optimization from Sparse-reward Offline Dataset
217. ICLR 2026Primal-Dual Policy Optimization for Adversarial Linear CMDPs
218. ICLR 2026Principled Fast and Meta Knowledge Learners for Continual Reinforcement Learning
219. ICLR 2026Probing in the Dark: State Entropy Maximization for POMDPs
220. ICLR 2026Probing to Refine: Reinforcement Distillation of LLM Reasoners via Explanatory Inversion
221. ICLR 2026Prompt Curriculum Learning for Efficient LLM Post-Training
222. ICLR 2026Q-Learning with Adjoint Matching
223. ICLR 2026Q-Learning with Fine-Grained Gap-Dependent Regret
224. ICLR 2026Q-learning with Posterior Sampling
225. ICLR 2026Q-RAG: Long Context Multi‑Step Retrieval via Value‑Based Embedder Training
226. ICLR 2026Quantile Advantage Estimation for Entropy-Safe Reasoning
227. ICLR 2026Queue Length Regret Bounds for Contextual Queueing Bandits
228. ICLR 2026R2-Dreamer: Redundancy-Reduced World Models without Decoders or Augmentation
229. ICLR 2026RD-HRL: Generating Reliable Sub-Goals for Long-Horizon Sparse-Reward Tasks
230. ICLR 2026REA-RL: Reflection-Aware Online Reinforcement Learning for Efficient Reasoning
231. ICLR 2026Reasoning as Representation: Rethinking Visual Reinforcement Learning in Image Quality Assessment
232. ICLR 2026Recurrent Action Transformer with Memory
233. ICLR 2026Reevaluating Policy Gradient Methods for Imperfect-Information Games
234. ICLR 2026Reference Guided Skill Discovery
235. ICLR 2026Refining Hybrid Genetic Search for CVRP via Reinforcement Learning-Finetuned LLM
236. ICLR 2026ReFORM: Reflected Flows for On-support Offline RL via Noise Manipulation
237. ICLR 2026Regret-Guided Search Control for Efficient Learning in AlphaZero
238. ICLR 2026Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models
239. ICLR 2026Reinforcement Learning for Machine Learning Engineering Agents
240. ICLR 2026Reinforcement Mid-Training
241. ICLR 2026Reinforcing Diffusion Models by Direct Group Preference Optimization
242. ICLR 2026Reinforcing General Reasoning Without Verifiers
243. ICLR 2026Relative Entropy Pathwise Policy Optimization
244. ICLR 2026Relative Value Learning
245. ICLR 2026Reliability-Adjusted Prioritized Experience Replay
246. ICLR 2026Replicable Reinforcement Learning with Linear Function Approximation
247. ICLR 2026Representation-Based Exploration for Language Models: From Test-Time to Post-Training
248. ICLR 2026RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
249. ICLR 2026Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcement
250. ICLR 2026Retaining Suboptimal Actions to Follow Shifting Optima in Multi-Agent 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.