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

411 papers, page 6 of 9

251. ICML 2025Combinatorial Reinforcement Learning with Preference Feedback
252. ICML 2025Conservative Offline Goal-Conditioned Implicit V-Learning
253. ICML 2025Constrained Exploitability Descent: An Offline Reinforcement Learning Method for Finding Mixed-Strategy Nash Equilibrium
254. ICML 2025Controlling Underestimation Bias in Constrained Reinforcement Learning for Safe Exploration
255. ICML 2025DIME: Diffusion-Based Maximum Entropy Reinforcement Learning
256. ICML 2025Directly Forecasting Belief for Reinforcement Learning with Delays
257. ICML 2025Distributionally Robust Policy Learning under Concept Drifts
258. ICML 2025Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
259. ICML 2025Empirical Design in Reinforcement Learning
260. ICML 2025Flow Q-Learning
261. ICML 2025Gradient Boosting Reinforcement Learning
262. ICML 2025Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning
263. ICML 2025Hierarchical Reinforcement Learning with Targeted Causal Interventions
264. ICML 2025Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals
265. ICML 2025Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning
266. ICML 2025Hyperspherical Normalization for Scalable Deep Reinforcement Learning
267. ICML 2025IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
268. ICML 2025Improving Transformer World Models for Data-Efficient RL
269. ICML 2025In-Context Reinforcement Learning From Suboptimal Historical Data
270. ICML 2025KEA: Keeping Exploration Alive by Proactively Coordinating Exploration Strategies
271. ICML 2025Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
272. ICML 2025Learning Policy Committees for Effective Personalization in MDPs with Diverse Tasks
273. ICML 2025Linear $Q$-Learning Does Not Diverge in $L^2$: Convergence Rates to a Bounded Set
274. ICML 2025Maximum Total Correlation Reinforcement Learning
275. ICML 2025Minimax Optimal Regret Bound for Reinforcement Learning with Trajectory Feedback
276. ICML 2025Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
277. ICML 2025Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization
278. ICML 2025Partially Observable Reinforcement Learning with Memory Traces
279. ICML 2025Policy Regularization on Globally Accessible States in Cross-Dynamics Reinforcement Learning
280. ICML 2025Polynomial-Time Approximability of Constrained Reinforcement Learning
281. ICML 2025Position: Constants are Critical in Regret Bounds for Reinforcement Learning
282. ICML 2025Position: General Intelligence Requires Reward-based Pretraining
283. ICML 2025Position: Lifetime tuning is incompatible with continual reinforcement learning
284. ICML 2025Provable Maximum Entropy Manifold Exploration via Diffusion Models
285. ICML 2025Provably Efficient Exploration in Inverse Constrained Reinforcement Learning
286. ICML 2025QPRL : Learning Optimal Policies with Quasi-Potential Functions for Asymmetric Traversal
287. ICML 2025Regret-Free Reinforcement Learning for Temporal Logic Specifications
288. ICML 2025Reinforcement Learning with Random Time Horizons
289. ICML 2025Reinforcement Learning with Segment Feedback
290. ICML 2025Reward Translation via Reward Machine in Semi-Alignable MDPs
291. ICML 2025Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs
292. ICML 2025Robust Offline Reinforcement Learning with Linearly Structured $f$-Divergence Regularization
293. ICML 2025RobustZero: Enhancing MuZero Reinforcement Learning Robustness to State Perturbations
294. ICML 2025Sleeping Reinforcement Learning
295. ICML 2025Stay Hungry, Keep Learning: Sustainable Plasticity for Deep Reinforcement Learning
296. ICML 2025Stealing That Free Lunch: Exposing the Limits of Dyna-Style Reinforcement Learning
297. ICML 2025Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks
298. ICML 2025The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning
299. ICML 2025The Impact of On-Policy Parallelized Data Collection on Deep Reinforcement Learning Networks
300. ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility 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.