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 10 of 17

451. ICLR 2025Leveraging Sub-Optimal Data for Human-in-the-Loop Reinforcement Learning
452. ICLR 2025Long-Short Decision Transformer: Bridging Global and Local Dependencies for Generalized Decision-Making
453. ICLR 2025Looking into User’s Long-term Interests through the Lens of Conservative Evidential Learning
454. ICLR 2025M^3PC: Test-time Model Predictive Control using Pretrained Masked Trajectory Model
455. ICLR 2025MA$^2$E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder
456. ICLR 2025MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL
457. ICLR 2025MaestroMotif: Skill Design from Artificial Intelligence Feedback
458. ICLR 2025MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization
459. ICLR 2025Minimax Optimal Reinforcement Learning with Quasi-Optimism
460. ICLR 2025Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
461. ICLR 2025Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization
462. ICLR 2025Model Risk-sensitive Offline Reinforcement Learning
463. ICLR 2025Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning
464. ICLR 2025Model-based RL as a Minimalist Approach to Horizon-Free and Second-Order Bounds
465. ICLR 2025Model-Free Offline Reinforcement Learning with Enhanced Robustness
466. ICLR 2025Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
467. ICLR 2025Multi-agent cooperation through learning-aware policy gradients
468. ICLR 2025Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
469. ICLR 2025Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form
470. ICLR 2025Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
471. ICLR 2025Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL
472. ICLR 2025Neuroplastic Expansion in Deep Reinforcement Learning
473. ICLR 2025Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
474. ICLR 2025Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
475. ICLR 2025Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning
476. ICLR 2025ODE-based Smoothing Neural Network for Reinforcement Learning Tasks
477. ICLR 2025Offline Hierarchical Reinforcement Learning via Inverse Optimization
478. ICLR 2025Offline RL in Regular Decision Processes: Sample Efficiency via Language Metrics
479. ICLR 2025Offline RL with Smooth OOD Generalization in Convex Hull and its Neighborhood
480. ICLR 2025OGBench: Benchmarking Offline Goal-Conditioned RL
481. ICLR 2025On Bits and Bandits: Quantifying the Regret-Information Trade-off
482. ICLR 2025On Generalization Across Environments In Multi-Objective Reinforcement Learning
483. ICLR 2025On Minimizing Adversarial Counterfactual Error in Adversarial Reinforcement Learning
484. ICLR 2025On Rollouts in Model-Based Reinforcement Learning
485. ICLR 2025On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations
486. ICLR 2025On the Modeling Capabilities of Large Language Models for Sequential Decision Making
487. ICLR 2025Online Reinforcement Learning in Non-Stationary Context-Driven Environments
488. ICLR 2025Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
489. ICLR 2025Online-to-Offline RL for Agent Alignment
490. ICLR 2025Open-World Reinforcement Learning over Long Short-Term Imagination
491. ICLR 2025Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
492. ICLR 2025Optimal Strong Regret and Violation in Constrained MDPs via Policy Optimization
493. ICLR 2025OptionZero: Planning with Learned Options
494. ICLR 2025ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
495. ICLR 2025Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
496. ICLR 2025PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
497. ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
498. ICLR 2025Policy Decorator: Model-Agnostic Online Refinement for Large Policy Model
499. ICLR 2025Policy Optimization under Imperfect Human Interactions with Agent-Gated Shared Autonomy
500. ICLR 2025PolyNet: Learning Diverse Solution Strategies for Neural Combinatorial Optimization

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.