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

146 papers, page 1 of 3

1. NeurIPS 2023A Definition of Continual Reinforcement Learning
2. NeurIPS 2023A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
3. NeurIPS 2023A Reduction-based Framework for Sequential Decision Making with Delayed Feedback
4. NeurIPS 2023A State Representation for Diminishing Rewards
5. NeurIPS 2023Accelerating Exploration with Unlabeled Prior Data
6. NeurIPS 2023Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
7. NeurIPS 2023Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
8. NeurIPS 2023Accelerating Value Iteration with Anchoring
9. NeurIPS 2023Accountability in Offline Reinforcement Learning: Explaining Decisions with a Corpus of Examples
10. NeurIPS 2023Adversarial Model for Offline Reinforcement Learning
11. NeurIPS 2023AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback
12. NeurIPS 2023Anytime-Competitive Reinforcement Learning with Policy Prior
13. NeurIPS 2023Bayesian Risk-Averse Q-Learning with Streaming Observations
14. NeurIPS 2023Belief Projection-Based Reinforcement Learning for Environments with Delayed Feedback
15. NeurIPS 2023Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets
16. NeurIPS 2023Bi-Level Offline Policy Optimization with Limited Exploration
17. NeurIPS 2023Budgeting Counterfactual for Offline RL
18. NeurIPS 2023CEIL: Generalized Contextual Imitation Learning
19. NeurIPS 2023Coherent Soft Imitation Learning
20. NeurIPS 2023Conditional Mutual Information for Disentangled Representations in Reinforcement Learning
21. NeurIPS 2023Conservative State Value Estimation for Offline Reinforcement Learning
22. NeurIPS 2023Constrained Policy Optimization with Explicit Behavior Density For Offline Reinforcement Learning
23. NeurIPS 2023Context Shift Reduction for Offline Meta-Reinforcement Learning
24. NeurIPS 2023Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning
25. NeurIPS 2023Corruption-Robust Offline Reinforcement Learning with General Function Approximation
26. NeurIPS 2023Counterfactual Conservative Q Learning for Offline Multi-agent Reinforcement Learning
27. NeurIPS 2023CQM: Curriculum Reinforcement Learning with a Quantized World Model
28. NeurIPS 2023Creating Multi-Level Skill Hierarchies in Reinforcement Learning
29. NeurIPS 2023Cross-Episodic Curriculum for Transformer Agents
30. NeurIPS 2023De novo Drug Design using Reinforcement Learning with Multiple GPT Agents
31. NeurIPS 2023Decision Stacks: Flexible Reinforcement Learning via Modular Generative Models
32. NeurIPS 2023Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
33. NeurIPS 2023Deep Reinforcement Learning with Plasticity Injection
34. NeurIPS 2023Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
35. NeurIPS 2023Discovering Hierarchical Achievements in Reinforcement Learning via Contrastive Learning
36. NeurIPS 2023Distributional Model Equivalence for Risk-Sensitive Reinforcement Learning
37. NeurIPS 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
38. NeurIPS 2023Doubly Robust Augmented Transfer for Meta-Reinforcement Learning
39. NeurIPS 2023Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
40. NeurIPS 2023Efficient Exploration in Continuous-time Model-based Reinforcement Learning
41. NeurIPS 2023Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric
42. NeurIPS 2023Elastic Decision Transformer
43. NeurIPS 2023ELDEN: Exploration via Local Dependencies
44. NeurIPS 2023f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences
45. NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
46. NeurIPS 2023Generative Modelling of Stochastic Actions with Arbitrary Constraints in Reinforcement Learning
47. NeurIPS 2023Gigastep - One Billion Steps per Second Multi-agent Reinforcement Learning
48. NeurIPS 2023Goal-Conditioned Predictive Coding for Offline Reinforcement Learning
49. NeurIPS 2023HIQL: Offline Goal-Conditioned RL with Latent States as Actions
50. NeurIPS 2023Hybrid Policy Optimization from Imperfect Demonstrations

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.