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 12 of 34

551. NeurIPS 2026Statistical Complexity of Soft Bellman Residual Minimization
552. NeurIPS 2026Temporal Consistency Improves Generalization in Contextual Offline Meta Reinforcement Learning
553. NeurIPS 2026TGRL: Temperature-Grouped Reinforcement Learning for Efficient Exploration in LLMs
554. NeurIPS 2026The Cost of Mismatch: Noise Amplification in Zeroth-Order Reinforcement Learning
555. NeurIPS 2026The Laplacian Keyboard: Beyond the Linear Span
556. NeurIPS 2026The Mirage of Optimizing Training Policies: Monotonic Inference Policies as the Real Objective for LLM Reinforcement Learning
557. NeurIPS 2026The Reasoning Boundary Paradox: How Reinforcement Learning Constrains Language Models
558. NeurIPS 2026The Sample Complexity of Multiple Change Point Identification under Bandit Feedback
559. NeurIPS 2026There are Levels to It: Red Teaming LLMs with Hierarchical Reinforcement Learning
560. NeurIPS 2026ToolSearcher: Optimizing Tool Selection at Scale via Reinforcement Learning
561. NeurIPS 2026Towards Convergence of PPO: An Approximate Descent Approach
562. NeurIPS 2026Towards Differentially Private Reinforcement Learning with General Function Approximation
563. NeurIPS 2026Towards Optimal Pre-training Data Mixtures for Empowering Reinforcement Learning in LLMs
564. NeurIPS 2026Trajectory-Consistent Diffusion Policies for Offline Reinforcement Learning
565. NeurIPS 2026Trust Region Q Adjoint Matching
566. NeurIPS 2026TrustFlow: Adaptive Trust Calibration for Language Model Guided Reinforcement Learning
567. NeurIPS 2026Uncertainty-Guided Reward Labeling for Reinforcement Learning under Limited Feedback
568. NeurIPS 2026Underlying Functional Structure of Reinforcement Learning
569. NeurIPS 2026Value-Rectified Distillation for Flow-based Offline Reinforcement Learning
570. NeurIPS 2026Variance-Averse n-Step Offline Reinforcement Learning for Sparse Long-Horizon Environments
571. NeurIPS 2026Variational Consequence-Driven Offline Reinforcement Learning
572. NeurIPS 2026Visual Reinforcement Fine-Tuning via Bootstrapped Medical Reasoning
573. NeurIPS 2026When Does Non-Uniform Replay Matter in Reinforcement Learning?
574. NeurIPS 2026When Policies Cannot Be Retrained: A Unified Closed-Form View of Post-Training Steering in Offline Reinforcement Learning
575. NeurIPS 2026Your Language Model is Its Own Critic: Reinforcement Learning with Value Estimation from Actor’s Internal States
576. CVPR 2025Automated Proof of Polynomial Inequalities via Reinforcement Learning
577. CVPR 2025Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards
578. ICLR 2025$\phi$-Update: A Class of Policy Update Methods with Policy Convergence Guarantee
579. ICLR 2025$q$-exponential family for policy optimization
580. ICLR 2025A Distributional Approach to Uncertainty-Aware Preference Alignment Using Offline Demonstrations
581. ICLR 2025A General Framework for Off-Policy Learning with Partially-Observed Reward
582. ICLR 2025A Generalist Hanabi Agent
583. ICLR 2025A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence
584. ICLR 2025A Single Goal is All You Need: Skills and Exploration Emerge from Contrastive RL without Rewards, Demonstrations, or Subgoals
585. ICLR 2025A Theoretical Framework for Partially-Observed Reward States in RLHF
586. ICLR 2025Accelerating Goal-Conditioned Reinforcement Learning Algorithms and Research
587. ICLR 2025Accelerating Task Generalisation with Multi-Level Skill Hierarchies
588. ICLR 2025ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample $V$-Ensemble
589. ICLR 2025ActSafe: Active Exploration with Safety Constraints for Reinforcement Learning
590. ICLR 2025Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning
591. ICLR 2025Advantage Alignment Algorithms
592. ICLR 2025Adversarial Policy Optimization for Offline Preference-based Reinforcement Learning
593. ICLR 2025An Optimal Discriminator Weighted Imitation Perspective for Reinforcement Learning
594. ICLR 2025Any-step Dynamics Model Improves Future Predictions for Online and Offline Reinforcement Learning
595. ICLR 2025Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
596. ICLR 2025BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
597. ICLR 2025Bayesian Analysis of Combinatorial Gaussian Process Bandits
598. ICLR 2025Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms
599. ICLR 2025Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning
600. ICLR 2025Beyond-Expert Performance with Limited Demonstrations: Efficient Imitation Learning with Double Exploration

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.