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 6 of 12

251. ICLR 2026Regret-Guided Search Control for Efficient Learning in AlphaZero
252. ICLR 2026Regularized Latent Dynamics Prediction is a Strong Baseline For Behavioral Foundation Models
253. ICLR 2026Reinforcement Learning for Machine Learning Engineering Agents
254. ICLR 2026Reinforcement Mid-Training
255. ICLR 2026Reinforcing Diffusion Models by Direct Group Preference Optimization
256. ICLR 2026Reinforcing General Reasoning Without Verifiers
257. ICLR 2026Relative Entropy Pathwise Policy Optimization
258. ICLR 2026Relative Value Learning
259. ICLR 2026Reliability-Adjusted Prioritized Experience Replay
260. ICLR 2026Replicable Reinforcement Learning with Linear Function Approximation
261. ICLR 2026Representation-Based Exploration for Language Models: From Test-Time to Post-Training
262. ICLR 2026RESCHED: Rethinking Flexible Job Shop Scheduling from a Transformer-based Architecture with Simplified States
263. ICLR 2026Resisting Contextual Interference in RAG via Parametric-Knowledge Reinforcement
264. ICLR 2026Retaining Suboptimal Actions to Follow Shifting Optima in Multi-Agent Reinforcement Learning
265. ICLR 2026Rethinking Policy Diversity in Ensemble Policy Gradient in Large-Scale Reinforcement Learning
266. ICLR 2026Revisiting Matrix Sketching in Linear Bandits: Achieving Sublinear Regret via Dyadic Block Sketching
267. ICLR 2026Revolutionizing Reinforcement Learning Framework for Diffusion Large Language Models
268. ICLR 2026Reward Is Enough: LLMs Are In-Context Reinforcement Learners
269. ICLR 2026Rewarding Doubt: A Reinforcement Learning Approach to Calibrated Confidence Expression of Large Language Models
270. ICLR 2026Risk-Sensitive Reinforcement Learning for Alleviating Exploration Dilemmas in Large Language Models
271. ICLR 2026RiskPO: Risk-based Policy Optimization with Verifiable Reward for LLM Post-Training
272. ICLR 2026RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
273. ICLR 2026RLVER: Reinforcement Learning with Verifiable Emotion Rewards for Empathetic Agents
274. ICLR 2026Robust Adaptive Multi-Step Predictive Shielding
275. ICLR 2026Robustness in the Face of Partial Identifiability in Reward Learning
276. ICLR 2026SAC Flow: Sample-Efficient Reinforcement Learning of Flow-Based Policies via Velocity-Reparameterized Sequential Modeling
277. ICLR 2026Safe Continuous-time Multi-Agent Reinforcement Learning via Epigraph Form
278. ICLR 2026Safe Exploration via Policy Priors
279. ICLR 2026SafeMPO: Constrained Reinforcement Learning with Probabilistic Incremental Improvement
280. ICLR 2026Sample Efficient Offline RL via T-Symmetry Enforced Latent State-Stitching
281. ICLR 2026Sample More to Think Less: Group Filtered Policy Optimization for Concise Reasoning
282. ICLR 2026Sample-efficient and Scalable Exploration in Continuous-Time RL
283. ICLR 2026Sample-Efficient Distributionally Robust Multi-Agent Reinforcement Learning via Online Interaction
284. ICLR 2026Scalable Exploration for High-Dimensional Continuous Control via Value-Guided Flow
285. ICLR 2026Scalable In-Context Q-Learning
286. ICLR 2026Scalable Offline Model-Based RL with Action Chunks
287. ICLR 2026Scaling Goal-conditioned Reinforcement Learning with Multistep Quasimetric Distances
288. ICLR 2026SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning
289. ICLR 2026Self-Aligned Reward: Towards Effective and Efficient Reasoners
290. ICLR 2026Self-Improving Skill Learning for Robust Skill-based Meta-Reinforcement Learning
291. ICLR 2026Self-Predictive Representations for Combinatorial Generalization in Behavioral Cloning
292. ICLR 2026SHAPO: Sharpness-Aware Policy Optimization for Safe Exploration
293. ICLR 2026SimpleTIR: End-to-End Reinforcement Learning for Multi-Turn Tool-Integrated Reasoning
294. ICLR 2026Simplicial Embeddings Improve Sample Efficiency in Actor–Critic Agents
295. ICLR 2026Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning
296. ICLR 2026Solving Football by Exploiting Equilibrium Structure of 2p0s Differential Games with One-Sided Information
297. ICLR 2026Solving General-Utility Markov Decision Processes in the Single-Trial Regime with Online Planning
298. ICLR 2026Solving Parameter-Robust Avoid Problems with Unknown Feasibility using Reinforcement Learning
299. ICLR 2026SPACeR: Self-Play Anchoring with Centralized Reference Models
300. ICLR 2026Sparse but Critical: A Token-Level Analysis of Distributional Shifts in RLVR Fine-Tuning of LLMs

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.