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 2 of 6

51. ICLR 2023Provably Efficient Lifelong Reinforcement Learning with Linear Representation
52. ICLR 2023Quality-Similar Diversity via Population Based Reinforcement Learning
53. ICLR 2023Quasi-optimal Reinforcement Learning with Continuous Actions
54. ICLR 2023Recursive Time Series Data Augmentation
55. ICLR 2023Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph Matching
56. ICLR 2023RLx2: Training a Sparse Deep Reinforcement Learning Model from Scratch
57. ICLR 2023ROCO: A General Framework for Evaluating Robustness of Combinatorial Optimization Solvers on Graphs
58. ICLR 2023Sample-Efficient Reinforcement Learning by Breaking the Replay Ratio Barrier
59. ICLR 2023Spectral Decomposition Representation for Reinforcement Learning
60. ICLR 2023TEMPERA: Test-Time Prompt Editing via Reinforcement Learning
61. ICLR 2023Temporal Disentanglement of Representations for Improved Generalisation in Reinforcement Learning
62. ICLR 2023The In-Sample Softmax for Offline Reinforcement Learning
63. ICLR 2023The Provable Benefit of Unsupervised Data Sharing for Offline Reinforcement Learning
64. ICLR 2023The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry
65. ICLR 2023Towards Minimax Optimal Reward-free Reinforcement Learning in Linear MDPs
66. ICLR 2023Transformer-based World Models Are Happy With 100k Interactions
67. ICLR 2023User-Interactive Offline Reinforcement Learning
68. ICLR 2023VIPeR: Provably Efficient Algorithm for Offline RL with Neural Function Approximation
69. ICLR 2023When Data Geometry Meets Deep Function: Generalizing Offline Reinforcement Learning
70. ICML 2023A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints
71. ICML 2023A Reinforcement Learning Framework for Dynamic Mediation Analysis
72. ICML 2023Adversarial Learning of Distributional Reinforcement Learning
73. ICML 2023An Investigation into Pre-Training Object-Centric Representations for Reinforcement Learning
74. ICML 2023Attention-Based Recurrence for Multi-Agent Reinforcement Learning under Stochastic Partial Observability
75. ICML 2023Automatic Intrinsic Reward Shaping for Exploration in Deep Reinforcement Learning
76. ICML 2023Beyond Exponentially Fast Mixing in Average-Reward Reinforcement Learning via Multi-Level Monte Carlo Actor-Critic
77. ICML 2023Boosting Offline Reinforcement Learning with Action Preference Query
78. ICML 2023Bootstrapped Representations in Reinforcement Learning
79. ICML 2023Constrained Decision Transformer for Offline Safe Reinforcement Learning
80. ICML 2023Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning
81. ICML 2023Differentially Private Episodic Reinforcement Learning with Heavy-tailed Rewards
82. ICML 2023Emergence of Adaptive Circadian Rhythms in Deep Reinforcement Learning
83. ICML 2023Enforcing Hard Constraints with Soft Barriers: Safe Reinforcement Learning in Unknown Stochastic Environments
84. ICML 2023Explaining Reinforcement Learning with Shapley Values
85. ICML 2023Flipping Coins to Estimate Pseudocounts for Exploration in Reinforcement Learning
86. ICML 2023GEAR: A GPU-Centric Experience Replay System for Large Reinforcement Learning Models
87. ICML 2023Hierarchical Programmatic Reinforcement Learning via Learning to Compose Programs
88. ICML 2023Identifiability and Generalizability in Constrained Inverse Reinforcement Learning
89. ICML 2023Improved Regret for Efficient Online Reinforcement Learning with Linear Function Approximation
90. ICML 2023Interactive Object Placement with Reinforcement Learning
91. ICML 2023Internally Rewarded Reinforcement Learning
92. ICML 2023Inverse Reinforcement Learning without Reinforcement Learning
93. ICML 2023Jump-Start Reinforcement Learning
94. ICML 2023Language Instructed Reinforcement Learning for Human-AI Coordination
95. ICML 2023LESSON: Learning to Integrate Exploration Strategies for Reinforcement Learning via an Option Framework
96. ICML 2023Mastering the Unsupervised Reinforcement Learning Benchmark from Pixels
97. ICML 2023Model-based Offline Reinforcement Learning with Count-based Conservatism
98. ICML 2023Model-based Reinforcement Learning with Scalable Composite Policy Gradient Estimators
99. ICML 2023Model-Bellman Inconsistency for Model-based Offline Reinforcement Learning
100. ICML 2023Model-Free Robust Average-Reward 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.