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 15 of 34

701. ICLR 2025Minimax Optimal Reinforcement Learning with Quasi-Optimism
702. ICLR 2025Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
703. ICLR 2025Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization
704. ICLR 2025Model Risk-sensitive Offline Reinforcement Learning
705. ICLR 2025Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning
706. ICLR 2025Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds
707. ICLR 2025Model-Free Offline Reinforcement Learning with Enhanced Robustness
708. ICLR 2025Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
709. ICLR 2025Multi-agent cooperation through learning-aware policy gradients
710. ICLR 2025Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
711. ICLR 2025Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
712. ICLR 2025Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
713. ICLR 2025Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL
714. ICLR 2025Neuroplastic Expansion in Deep Reinforcement Learning
715. ICLR 2025Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
716. ICLR 2025Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
717. ICLR 2025Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
718. ICLR 2025ODE-based Smoothing Neural Network for Reinforcement Learning Tasks
719. ICLR 2025Offline Hierarchical Reinforcement Learning via Inverse Optimization
720. ICLR 2025Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics
721. ICLR 2025Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
722. ICLR 2025OGBench: Benchmarking Offline Goal-Conditioned RL
723. ICLR 2025On Bits and Bandits: Quantifying the Regret-Information Trade-off
724. ICLR 2025On Generalization Across Environments In Multi-Objective Reinforcement Learning
725. ICLR 2025On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
726. ICLR 2025On Rollouts in Model-Based Reinforcement Learning
727. ICLR 2025On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
728. ICLR 2025On the Modeling Capabilities of Large Language Models for Sequential Decision Making
729. ICLR 2025Online Reinforcement Learning in Non-Stationary Context-Driven Environments
730. ICLR 2025Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
731. ICLR 2025Online-to-Offline RL for Agent Alignment
732. ICLR 2025Open-World Reinforcement Learning over Long Short-Term Imagination
733. ICLR 2025Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
734. ICLR 2025Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
735. ICLR 2025OptionZero: Planning with Learned Options
736. ICLR 2025ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
737. ICLR 2025Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
738. ICLR 2025PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
739. ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
740. ICLR 2025Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model
741. ICLR 2025Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy
742. ICLR 2025PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization
743. ICLR 2025POTEC: Off-Policy Contextual Bandits for Large Action Spaces via Policy Decomposition
744. ICLR 2025Preference Elicitation for Offline Reinforcement Learning
745. ICLR 2025Prevalence of Negative Transfer in Continual Reinforcement Learning: Analyses and a Simple Baseline
746. ICLR 2025Prioritized Generative Replay
747. ICLR 2025PWM: Policy Learning with Multi-Task World Models
748. ICLR 2025Q-Adapter: Customizing Pre-trained LLMs to New Preferences with Forgetting Mitigation
749. ICLR 2025Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning
750. ICLR 2025QMP: Q-switch Mixture of Policies for Multi-Task Behavior Sharing

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.