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

847 papers, page 2 of 17

51. ICLR 2026Combinatorial Rising Bandits
52. ICLR 2026ContextIF: Enhancing Instruction-Following through Context Reward
53. ICLR 2026Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
54. ICLR 2026Continuous-Time Value Iteration for Multi-Agent Reinforcement Learning
55. ICLR 2026Convergence of an actor-critic gradient flow for entropy regularised MDPs in general spaces
56. ICLR 2026ConvRec-R1: Training LLM-based Conversational Recommender Systems with Reinforcement Learning
57. ICLR 2026Correlated Policy Optimization in Multi-Agent Subteams
58. ICLR 2026Critique-Coder: Enhancing Coder Models by Critique Reinforcement Learning
59. ICLR 2026Cross-Domain Policy Optimization via Bellman Consistency and Hybrid Critics
60. ICLR 2026Cross-Embodied Co-Design for Dexterous Hands
61. ICLR 2026Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets
62. ICLR 2026Curriculum Reinforcement Learning from Easy to Hard Tasks Improves LLM Reasoning
63. ICLR 2026DEAS: DEtached value learning with Action Sequence for Scalable Offline RL
64. ICLR 2026Decision Pre-Trained Transformer is a Scalable In-Context Reinforcement Learner
65. ICLR 2026Decoupled Q-Chunking
66. ICLR 2026Deep SPI: Safe Policy Improvement via World Models
67. ICLR 2026DeepCompress: A Dual Reward Strategy for Dynamically Exploring and Compressing Reasoning Chains
68. ICLR 2026Demystifying Emergent Exploration in Goal-Conditioned RL
69. ICLR 2026DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment
70. ICLR 2026Designing Time Series Experiments in A/B Testing with Transformer Reinforcement Learning
71. ICLR 2026Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
72. ICLR 2026Dichotomous Diffusion Policy Optimization
73. ICLR 2026Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach
74. ICLR 2026Discovering Diverse Behaviors via Temporal Contrastive Learning
75. ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
76. ICLR 2026Displacement-Resistant Extensions of DPO with Nonconvex $f$-Divergences
77. ICLR 2026Distributional value gradients for stochastic environments
78. ICLR 2026Distributionally Robust Cooperative Multi-agent Reinforcement Learning with Value Factorization
79. ICLR 2026Distributions as Actions: A Unified Framework for Diverse Action Spaces
80. ICLR 2026Diversity-Aware Online Prompt Assignment to Generative Models
81. ICLR 2026Does “Do Differentiable Simulators Give Better Policy Gradients?” Give Better Policy Gradients?
82. ICLR 2026DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
83. ICLR 2026DR-SAC: Distributionally Robust Soft Actor-Critic for Reinforcement Learning under Uncertainty
84. ICLR 2026Dual Goal Representations
85. ICLR 2026Dual-Objective Reinforcement Learning with Novel Hamilton-Jacobi-Bellman Formulations
86. ICLR 2026Dual-Robust Cross-Domain Offline Reinforcement Learning Against Dynamics Shifts
87. ICLR 2026Efficient Morphology–Control Co-Design via Stackelberg PPO under Non-Differentiable Leader–Follower Interfaces
88. ICLR 2026Efficient Offline Reinforcement Learning via Peer-Influenced Constraint
89. ICLR 2026Efficient Reinforcement Learning by Guiding World Models with Non-Curated Data
90. ICLR 2026Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL
91. ICLR 2026ELMUR: External Layer Memory with Update/Rewrite for Long-Horizon RL
92. ICLR 2026EMFuse: Energy-based Model Fusion for Decision Making
93. ICLR 2026Enhancing Geometric Perception in VLMs via Translator-Guided Reinforcement Learning
94. ICLR 2026Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs
95. ICLR 2026Entropy Regularizing Activation: Boosting Continuous Control, Large Language Models, and Image Classification with Activation as Entropy Constraints
96. ICLR 2026Entropy-preserving reinforcement learning
97. ICLR 2026EUBRL: Epistemic Uncertainty Directed Bayesian Reinforcement Learning
98. ICLR 2026Exploratory Diffusion Model for Unsupervised Reinforcement Learning
99. ICLR 2026Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization
100. ICLR 2026EXPO: Stable Reinforcement Learning with Expressive Policies

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.