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

287 papers, page 1 of 6

1. CVPR 2023Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning
2. CVPR 2023Fusing Pre-Trained Language Models With Multimodal Prompts Through Reinforcement Learning
3. CVPR 2023Local-Guided Global: Paired Similarity Representation for Visual Reinforcement Learning
4. ICLR 2023A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning
5. ICLR 2023Asymptotic Instance-Optimal Algorithms for Interactive Decision Making
6. ICLR 2023Backstepping Temporal Difference Learning
7. ICLR 2023BC-IRL: Learning Generalizable Reward Functions from Demonstrations
8. ICLR 2023Become a Proficient Player with Limited Data through Watching Pure Videos
9. ICLR 2023Behavior Prior Representation learning for Offline Reinforcement Learning
10. ICLR 2023Benchmarking Constraint Inference in Inverse Reinforcement Learning
11. ICLR 2023Benchmarking Offline Reinforcement Learning on Real-Robot Hardware
12. ICLR 2023Can Agents Run Relay Race with Strangers? Generalization of RL to Out-of-Distribution Trajectories
13. ICLR 2023CLARE: Conservative Model-Based Reward Learning for Offline Inverse Reinforcement Learning
14. ICLR 2023Confidence-Conditioned Value Functions for Offline Reinforcement Learning
15. ICLR 2023Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
16. ICLR 2023Decision Transformer under Random Frame Dropping
17. ICLR 2023Deep Reinforcement Learning for Cost-Effective Medical Diagnosis
18. ICLR 2023Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
19. ICLR 2023Distributional Meta-Gradient Reinforcement Learning
20. ICLR 2023Efficient Deep Reinforcement Learning Requires Regulating Overfitting
21. ICLR 2023Extreme Q-Learning: MaxEnt RL without Entropy
22. ICLR 2023Gray-Box Gaussian Processes for Automated Reinforcement Learning
23. ICLR 2023Guiding Safe Exploration with Weakest Preconditions
24. ICLR 2023Harnessing Mixed Offline Reinforcement Learning Datasets via Trajectory Weighting
25. ICLR 2023HiT-MDP: Learning the SMDP option framework on MDPs with Hidden Temporal Embeddings
26. ICLR 2023Human-level Atari 200x faster
27. ICLR 2023Hyperbolic Deep Reinforcement Learning
28. ICLR 2023Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs
29. ICLR 2023In-context Reinforcement Learning with Algorithm Distillation
30. ICLR 2023In-sample Actor Critic for Offline Reinforcement Learning
31. ICLR 2023Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function
32. ICLR 2023Latent Variable Representation for Reinforcement Learning
33. ICLR 2023Learning About Progress From Experts
34. ICLR 2023Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model
35. ICLR 2023Learning Soft Constraints From Constrained Expert Demonstrations
36. ICLR 2023LS-IQ: Implicit Reward Regularization for Inverse Reinforcement Learning
37. ICLR 2023Minimum Description Length Control
38. ICLR 2023MoDem: Accelerating Visual Model-Based Reinforcement Learning with Demonstrations
39. ICLR 2023Near-Optimal Adversarial Reinforcement Learning with Switching Costs
40. ICLR 2023Near-Optimal Deployment Efficiency in Reward-Free Reinforcement Learning with Linear Function Approximation
41. ICLR 2023Near-optimal Policy Identification in Active Reinforcement Learning
42. ICLR 2023Neural Episodic Control with State Abstraction
43. ICLR 2023Offline Reinforcement Learning with Differentiable Function Approximation is Provably Efficient
44. ICLR 2023Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization
45. ICLR 2023On the Robustness of Safe Reinforcement Learning under Observational Perturbations
46. ICLR 2023Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
47. ICLR 2023PAC Reinforcement Learning for Predictive State Representations
48. ICLR 2023Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
49. ICLR 2023Pink Noise Is All You Need: Colored Noise Exploration in Deep Reinforcement Learning
50. ICLR 2023POPGym: Benchmarking Partially Observable Reinforcement Learning

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.