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

1,676 papers, page 28 of 34

1351. NeurIPS 2024PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning
1352. NeurIPS 2024Provable Partially Observable Reinforcement Learning with Privileged Information
1353. NeurIPS 2024Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
1354. NeurIPS 2024Provably Efficient Reinforcement Learning with Multinomial Logit Function Approximation
1355. NeurIPS 2024Q-Distribution guided Q-learning for offline reinforcement learning: Uncertainty penalized Q-value via consistency model
1356. NeurIPS 2024Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation
1357. NeurIPS 2024REBEL: Reinforcement Learning via Regressing Relative Rewards
1358. NeurIPS 2024Recurrent Reinforcement Learning with Memoroids
1359. NeurIPS 2024Regularized Q-Learning
1360. NeurIPS 2024Reinforcement Learning with Adaptive Regularization for Safe Control of Critical Systems
1361. NeurIPS 2024Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control
1362. NeurIPS 2024Reinforcement Learning with Lookahead Information
1363. NeurIPS 2024Rethinking Exploration in Reinforcement Learning with Effective Metric-Based Exploration Bonus
1364. NeurIPS 2024Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
1365. NeurIPS 2024Rethinking Optimal Transport in Offline Reinforcement Learning
1366. NeurIPS 2024Robust Reinforcement Learning with General Utility
1367. NeurIPS 2024Sample-Efficient Constrained Reinforcement Learning with General Parameterization
1368. NeurIPS 2024Simplifying Constraint Inference with Inverse Reinforcement Learning
1369. NeurIPS 2024Simplifying Latent Dynamics with Softly State-Invariant World Models
1370. NeurIPS 2024Solving Minimum-Cost Reach Avoid using Reinforcement Learning
1371. NeurIPS 2024Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs
1372. NeurIPS 2024Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
1373. NeurIPS 2024SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning
1374. NeurIPS 2024State Chrono Representation for Enhancing Generalization in Reinforcement Learning
1375. NeurIPS 2024State-free Reinforcement Learning
1376. NeurIPS 2024Statistical Efficiency of Distributional Temporal Difference Learning
1377. NeurIPS 2024Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning
1378. NeurIPS 2024Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning
1379. NeurIPS 2024Swift Sampler: Efficient Learning of Sampler by 10 Parameters
1380. NeurIPS 2024Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces
1381. NeurIPS 2024The Edge-of-Reach Problem in Offline Model-Based Reinforcement Learning
1382. NeurIPS 2024The Surprising Ineffectiveness of Pre-Trained Visual Representations for Model-Based Reinforcement Learning
1383. NeurIPS 2024The Value of Reward Lookahead in Reinforcement Learning
1384. NeurIPS 2024Time-Constrained Robust MDPs
1385. NeurIPS 2024Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning
1386. NeurIPS 2024Unlock the Intermittent Control Ability of Model Free Reinforcement Learning
1387. NeurIPS 2024Using Unity to Help Solve Reinforcement Learning
1388. NeurIPS 2024Worst-Case Offline Reinforcement Learning with Arbitrary Data Support
1389. NeurIPS 2024XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX
1390. CVPR 2023Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
1391. CVPR 2023Fusing Pre-Trained Language Models With Multimodal Prompts Through Reinforcement Learning
1392. CVPR 2023Local-Guided Global: Paired Similarity Representation for Visual Reinforcement Learning
1393. ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
1394. ICLR 2023Asymptotic Instance-Optimal Algorithms for Interactive Decision Making
1395. ICLR 2023Backstepping Temporal Difference Learning
1396. ICLR 2023BC-IRL: Learning Generalizable Reward Functions from Demonstrations
1397. ICLR 2023Become a Proficient Player with Limited Data through Watching Pure Videos
1398. ICLR 2023Behavior Prior Representation learning for Offline Reinforcement Learning
1399. ICLR 2023Benchmarking Constraint Inference in Inverse Reinforcement Learning
1400. ICLR 2023Benchmarking Offline Reinforcement Learning on Real-Robot Hardware

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.