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 13 / 17 页

601. ICLR 2024Deep Reinforcement Learning for Modelling Protein Complexes
602. ICLR 2024Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
603. ICLR 2024Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
604. ICLR 2024Demonstration-Regularized RL
605. ICLR 2024Demystifying Linear MDPs and Novel Dynamics Aggregation Framework
606. ICLR 2024Discovering Temporally-Aware Reinforcement Learning Algorithms
607. ICLR 2024DittoGym: Learning to Control Soft Shape-Shifting Robots
608. ICLR 2024Diverse Projection Ensembles for Distributional Reinforcement Learning
609. ICLR 2024DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations
610. ICLR 2024Domain Randomization via Entropy Maximization
611. ICLR 2024DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
612. ICLR 2024DrM: Mastering Visual Reinforcement Learning through Dormant Ratio Minimization
613. ICLR 2024DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks
614. ICLR 2024Dual RL: Unification and New Methods for Reinforcement and Imitation Learning
615. ICLR 2024Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces
616. ICLR 2024Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
617. ICLR 2024Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning
618. ICLR 2024Efficient Inverse Multiagent Learning
619. ICLR 2024Efficient Multi-agent Reinforcement Learning by Planning
620. ICLR 2024Efficient Planning with Latent Diffusion
621. ICLR 2024Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain
622. ICLR 2024Entity-Centric Reinforcement Learning for Object Manipulation from Pixels
623. ICLR 2024Eureka: Human-Level Reward Design via Coding Large Language Models
624. ICLR 2024Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
625. ICLR 2024Fast Imitation via Behavior Foundation Models
626. ICLR 2024Fast Value Tracking for Deep Reinforcement Learning
627. ICLR 2024Federated Q-Learning: Linear Regret Speedup with Low Communication Cost
628. ICLR 2024Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
629. ICLR 2024Fixed-Budget Differentially Private Best Arm Identification
630. ICLR 2024Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation
631. ICLR 2024Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning
632. ICLR 2024Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
633. ICLR 2024Goodhart's Law in Reinforcement Learning
634. ICLR 2024GROOT: Learning to Follow Instructions by Watching Gameplay Videos
635. ICLR 2024Hindsight PRIORs for Reward Learning from Human Preferences
636. ICLR 2024Horizon-free Reinforcement Learning in Adversarial Linear Mixture MDPs
637. ICLR 2024Identifying Policy Gradient Subspaces
638. ICLR 2024Illusory Attacks: Information-theoretic detectability matters in adversarial attacks
639. ICLR 2024Imitation Learning from Observation with Automatic Discount Scheduling
640. ICLR 2024Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
641. ICLR 2024Improving Intrinsic Exploration by Creating Stationary Objectives
642. ICLR 2024Improving Offline RL by Blending Heuristics
643. ICLR 2024In-context Exploration-Exploitation for Reinforcement Learning
644. ICLR 2024Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
645. ICLR 2024Intelligent Switching for Reset-Free RL
646. ICLR 2024Jumanji: a Diverse Suite of Scalable Reinforcement Learning Environments in JAX
647. ICLR 2024Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
648. ICLR 2024Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks
649. ICLR 2024Language Model Self-improvement by Reinforcement Learning Contemplation
650. ICLR 2024Learning Decentralized Partially Observable Mean Field Control for Artificial Collective Behavior

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。