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

403 papers, page 7 of 9

301. ICML 2024When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
302. ICML 2024Zero-Sum Positional Differential Games as a Framework for Robust Reinforcement Learning: Deep Q-Learning Approach
303. NeurIPS 2024A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning
304. NeurIPS 2024A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
305. NeurIPS 2024A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
306. NeurIPS 2024A theoretical case-study of Scalable Oversight in Hierarchical Reinforcement Learning
307. NeurIPS 2024A Unified Principle of Pessimism for Offline Reinforcement Learning under Model Mismatch
308. NeurIPS 2024A2PO: Towards Effective Offline Reinforcement Learning from an Advantage-aware Perspective
309. NeurIPS 2024Achieving Constant Regret in Linear Markov Decision Processes
310. NeurIPS 2024Achieving Tractable Minimax Optimal Regret in Average Reward MDPs
311. NeurIPS 2024Adam on Local Time: Addressing Nonstationarity in RL with Relative Adam Timesteps
312. NeurIPS 2024Adaptive Exploration for Data-Efficient General Value Function Evaluations
313. NeurIPS 2024Adversarially Trained Weighted Actor-Critic for Safe Offline Reinforcement Learning
314. NeurIPS 2024Beyond Optimism: Exploration With Partially Observable Rewards
315. NeurIPS 2024CALE: Continuous Arcade Learning Environment
316. NeurIPS 2024Compositional Automata Embeddings for Goal-Conditioned Reinforcement Learning
317. NeurIPS 2024Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning
318. NeurIPS 2024Diffusion Imitation from Observation
319. NeurIPS 2024Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning
320. NeurIPS 2024Diffusion-based Curriculum Reinforcement Learning
321. NeurIPS 2024Diffusion-DICE: In-Sample Diffusion Guidance for Offline Reinforcement Learning
322. NeurIPS 2024Distributional Reinforcement Learning with Regularized Wasserstein Loss
323. NeurIPS 2024Doubly Mild Generalization for Offline Reinforcement Learning
324. NeurIPS 2024Dual Critic Reinforcement Learning under Partial Observability
325. NeurIPS 2024Dynamic Model Predictive Shielding for Provably Safe Reinforcement Learning
326. NeurIPS 2024DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning
327. NeurIPS 2024Efficient Reinforcement Learning by Discovering Neural Pathways
328. NeurIPS 2024Enhancing Robustness in Deep Reinforcement Learning: A Lyapunov Exponent Approach
329. NeurIPS 2024Exclusively Penalized Q-learning for Offline Reinforcement Learning
330. NeurIPS 2024Exploiting the Replay Memory Before Exploring the Environment: Enhancing Reinforcement Learning Through Empirical MDP Iteration
331. NeurIPS 2024Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning
332. NeurIPS 2024Federated Ensemble-Directed Offline Reinforcement Learning
333. NeurIPS 2024First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs
334. NeurIPS 2024Foundations of Multivariate Distributional Reinforcement Learning
335. NeurIPS 2024Goal Conditioned Reinforcement Learning for Photo Finishing Tuning
336. NeurIPS 2024Goal-Conditioned On-Policy Reinforcement Learning
337. NeurIPS 2024How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach
338. NeurIPS 2024How to Solve Contextual Goal-Oriented Problems with Offline Datasets?
339. NeurIPS 2024Hybrid Reinforcement Learning Breaks Sample Size Barriers In Linear MDPs
340. NeurIPS 2024Identifying Latent State-Transition Processes for Individualized Reinforcement Learning
341. NeurIPS 2024Implicit Curriculum in Procgen Made Explicit
342. NeurIPS 2024In-Trajectory Inverse Reinforcement Learning: Learn Incrementally Before an Ongoing Trajectory Terminates
343. NeurIPS 2024Is Value Learning Really the Main Bottleneck in Offline RL?
344. NeurIPS 2024Iteratively Refined Behavior Regularization for Offline Reinforcement Learning
345. NeurIPS 2024KALM: Knowledgeable Agents by Offline Reinforcement Learning from Large Language Model Rollouts
346. NeurIPS 2024Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
347. NeurIPS 2024Last-Iterate Global Convergence of Policy Gradients for Constrained Reinforcement Learning
348. NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
349. NeurIPS 2024Learning Goal-Conditioned Representations for Language Reward Models
350. NeurIPS 2024Local Linearity: the Key for No-regret Reinforcement Learning in Continuous MDPs

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.