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 6 of 7

251. ICML 2024Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
252. ICML 2024SHINE: Shielding Backdoors in Deep Reinforcement Learning
253. ICML 2024Simple Ingredients for Offline Reinforcement Learning
254. ICML 2024Single-Trajectory Distributionally Robust Reinforcement Learning
255. ICML 2024SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning
256. ICML 2024Switching the Loss Reduces the Cost in Batch Reinforcement Learning
257. ICML 2024Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learning
258. ICML 2024Test-Time Regret Minimization in Meta Reinforcement Learning
259. ICML 2024To the Max: Reinventing Reward in Reinforcement Learning
260. ICML 2024Towards Global Optimality for Practical Average Reward Reinforcement Learning without Mixing Time Oracles
261. ICML 2024Towards Robust Model-Based Reinforcement Learning Against Adversarial Corruption
262. ICML 2024Uncertainty-Aware Reward-Free Exploration with General Function Approximation
263. ICML 2024Unlock the Cognitive Generalization of Deep Reinforcement Learning via Granular Ball Representation
264. ICML 2024Value-Evolutionary-Based Reinforcement Learning
265. ICML 2024When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
266. ICML 2024Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach
267. ICML 2023A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints
268. ICML 2023A Reinforcement Learning Framework for Dynamic Mediation Analysis
269. ICML 2023Adversarial Learning of Distributional Reinforcement Learning
270. ICML 2023An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning
271. ICML 2023Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability
272. ICML 2023Automatic Intrinsic Reward Shaping for Exploration in Deep Reinforcement Learning
273. ICML 2023Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic
274. ICML 2023Boosting Offline Reinforcement Learning with Action Preference Query
275. ICML 2023Bootstrapped Representations in Reinforcement Learning
276. ICML 2023Constrained Decision Transformer for Offline Safe Reinforcement Learning
277. ICML 2023Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning
278. ICML 2023Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
279. ICML 2023Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning
280. ICML 2023Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
281. ICML 2023Explaining Reinforcement Learning with Shapley Values
282. ICML 2023Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning
283. ICML 2023GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
284. ICML 2023Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs
285. ICML 2023Identifiability and Generalizability in Constrained Inverse Reinforcement Learning
286. ICML 2023Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation
287. ICML 2023Interactive Object Placement with Reinforcement Learning
288. ICML 2023Internally Rewarded Reinforcement Learning
289. ICML 2023Inverse Reinforcement Learning without Reinforcement Learning
290. ICML 2023Jump-Start Reinforcement Learning
291. ICML 2023Language Instructed Reinforcement Learning for Human-AI Coordination
292. ICML 2023LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
293. ICML 2023Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
294. ICML 2023Model-based Offline Reinforcement Learning with Count-based Conservatism
295. ICML 2023Model-based Reinforcement Learning with Scalable Composite Policy Gradient Estimators
296. ICML 2023Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning
297. ICML 2023Model-Free Robust Average-Reward Reinforcement Learning
298. ICML 2023Near-Minimax-Optimal Risk-Sensitive Reinforcement Learning with CVaR
299. ICML 2023Near-optimal Conservative Exploration in Reinforcement Learning under Episode-wise Constraints
300. ICML 2023Nearly Minimax Optimal Reinforcement Learning for Linear Markov Decision Processes

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.