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 1,676 篇，第 16 / 34 页

751. ICLR 2025Reconstruction-Guided Policy: Enhancing Decision-Making through Agent-Wise State Consistency
752. ICLR 2025REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context in New Environments
753. ICLR 2025Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF
754. ICLR 2025Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
755. ICLR 2025Reinforcement learning with combinatorial actions for coupled restless bandits
756. ICLR 2025Residual Kernel Policy Network: Enhancing Stability and Robustness in RKHS-Based Reinforcement Learning
757. ICLR 2025Revisiting a Design Choice in Gradient Temporal Difference Learning
758. ICLR 2025REvolve: Reward Evolution with Large Language Models using Human Feedback
759. ICLR 2025Reward Dimension Reduction for Scalable Multi-Objective Reinforcement Learning
760. ICLR 2025Reward Learning from Multiple Feedback Types
761. ICLR 2025Risk-Sensitive Variational Actor-Critic: A Model-Based Approach
762. ICLR 2025Robust Transfer of Safety-Constrained Reinforcement Learning Agents
763. ICLR 2025RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
764. ICLR 2025Safety Representations for Safer Policy Learning
765. ICLR 2025Safety-Prioritizing Curricula for Constrained Reinforcement Learning
766. ICLR 2025Scalable Decision-Making in Stochastic Environments through Learned Temporal Abstraction
767. ICLR 2025Scaling Offline Model-Based RL via Jointly-Optimized World-Action Model Pretraining
768. ICLR 2025Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement Learning
769. ICLR 2025Select before Act: Spatially Decoupled Action Repetition for Continuous Control
770. ICLR 2025SELF-EVOLVED REWARD LEARNING FOR LLMS
771. ICLR 2025Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning
772. ICLR 2025SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation
773. ICLR 2025SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
774. ICLR 2025Simple, Good, Fast: Self-Supervised World Models Free of Baggage
775. ICLR 2025Simplifying Deep Temporal Difference Learning
776. ICLR 2025SmartRAG: Jointly Learn RAG-Related Tasks From the Environment Feedback
777. ICLR 2025Solving New Tasks by Adapting Internet Video Knowledge
778. ICLR 2025Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation
779. ICLR 2025Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
780. ICLR 2025Student-Informed Teacher Training
781. ICLR 2025Studying the Interplay Between the Actor and Critic Representations in Reinforcement Learning
782. ICLR 2025Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search
783. ICLR 2025Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
784. ICLR 2025Temporal Difference Learning: Why It Can Be Fast and How It Will Be Faster
785. ICLR 2025The Value of Sensory Information to a Robot
786. ICLR 2025TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning
787. ICLR 2025Toward Efficient Multi-Agent Exploration With Trajectory Entropy Maximization
788. ICLR 2025Towards Empowerment Gain through Causal Structure Learning in Model-Based Reinforcement Learning
789. ICLR 2025Towards General-Purpose Model-Free Reinforcement Learning
790. ICLR 2025Towards Generalizable Reinforcement Learning via Causality-Guided Self-Adaptive Representations
791. ICLR 2025TPO: Aligning Large Language Models with Multi-branch & Multi-step Preference Trees
792. ICLR 2025Training Language Models to Self-Correct via Reinforcement Learning
793. ICLR 2025Training Large Language Models for Retrieval-Augmented Question Answering through Backtracking Correction
794. ICLR 2025Trajectory-Class-Aware Multi-Agent Reinforcement Learning
795. ICLR 2025Transformers Can Learn Temporal Difference Methods for In-Context Reinforcement Learning
796. ICLR 2025Uncertainty and Influence aware Reward Model Refinement for Reinforcement Learning from Human Feedback
797. ICLR 2025Understanding Constraint Inference in Safety-Critical Inverse Reinforcement Learning
798. ICLR 2025UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP
799. ICLR 2025Utilitarian Algorithm Configuration for Infinite Parameter Spaces
800. ICLR 2025UTILITY: Utilizing Explainable Reinforcement Learning to Improve Reinforcement Learning

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。