通用机器学习 · reinforcement learning论文趋势 2023–2026

主要结论

• 通用机器学习 · reinforcement learning论文从 2023 年的 287 篇增长到 2026 年的 575 篇，三年间扩大到约 2.0 倍。
• ICLR 是发通用机器学习 · reinforcement learning论文最多的会议，2023–2026 年共 847 篇，占四个会议总量的 51%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 34 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 2；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · reinforcement learning是 2.0 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部通用机器学习 · reinforcement learning论文

共 847 篇，第 10 / 17 页

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

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · reinforcement learning论文？

共 1,676 篇，按年份分别是 2023 年 287 篇、2024 年 403 篇、2025 年 411 篇、2026 年 575 篇。

NeurIPS 2026 有多少篇通用机器学习 · reinforcement learning论文？

NeurIPS 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 108 篇。

ICLR 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICLR 2026 有 335 篇通用机器学习 · reinforcement learning论文，上一届是 230 篇。

ICML 2026 有多少篇通用机器学习 · reinforcement learning论文？

ICML 2026 有 113 篇通用机器学习 · reinforcement learning论文，上一届是 71 篇。

CVPR 2026 有多少篇通用机器学习 · reinforcement learning论文？

CVPR 2026 有 14 篇通用机器学习 · reinforcement learning论文，上一届是 2 篇。

哪个会议的通用机器学习 · reinforcement learning论文最多？

ICLR，2023–2026 年共 847 篇。