探索利用论文趋势 2023–2026

主要结论

• 探索利用论文从 2023 年的 47 篇增长到 2026 年的 71 篇，三年间扩大到约 1.5 倍。
• NeurIPS 是发探索利用论文最多的会议，2023–2026 年共 93 篇，占四个会议总量的 40%。
• 交叉方向里涨得最快的是推理模型：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 10 篇。
• 在「推荐与广告」的 5 个主题里，它的 2026 年论文数排第 4；同组增长最快的点击率预测是 2.6 倍，探索利用是 1.5 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 2026Decentralized Q-Learning in Markov Potential Games
• ICML 2026Bandit Social Leaning Dynamics with Exploration Episodes
• ICLR 2026Laplacian Kernelized Bandit
• CVPR 2026Underground Plant Exploration Non-Destructive 3D Root Assessment with GPR Based
• NeurIPS 2025DUET: Dual-Perspective Pseudo Labeling and Uncertainty-aware Exploration & Exploitation Training for Source-Free Domain Adaptation
• ICML 2025Clustering Items through Bandit Feedback: Finding the Right Feature out of Many
• ICLR 2025B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners
• CVPR 2025Dynamic Pseudo Labeling via Gradient Cutting for High-Low Entropy Exploration
• NeurIPS 2024Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment
• ICML 2024A Contextual Combinatorial Bandit Approach to Negotiation
• ICLR 2024Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation
• CVPR 2024Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation
• NeurIPS 2023Adaptive Algorithms for Relaxed Pareto Set Identification
• ICML 2023Curiosity in Hindsight: Intrinsic Exploration in Stochastic Environments
• ICLR 2023Combinatorial Pure Exploration of Causal Bandits
• CVPR 2023Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields
• NeurIPS 2026Hit Expansion via Localized Exploration of Synthesizable Chemical Space
• ICML 2026Exploration-free Algorithms for Multi-group Mean Estimation
• ICLR 2026DIVERSE: Disagreement-Inducing Vector Evolution for Rashomon Set Exploration
• CVPR 2026From Exploration to Exploitation A Two-Stage Entropy RLVR Approach for

全部探索利用论文

共 63 篇，第 1 / 2 页

1. CVPR 2024Accept the Modality Gap: An Exploration in the Hyperbolic Space
2. CVPR 2024Instance-aware Exploration-Verification-Exploitation for Instance ImageGoal Navigation
3. ICLR 2024Dropout-Based Rashomon Set Exploration for Efficient Predictive Multiplicity Estimation
4. ICLR 2024Improving Intrinsic Exploration by Creating Stationary Objectives
5. ICLR 2024In-context Exploration-Exploitation for Reinforcement Learning
6. ICLR 2024Neural Active Learning Beyond Bandits
7. ICLR 2024The Curse of Diversity in Ensemble-Based Exploration
8. ICLR 2024Unlocking the Power of Representations in Long-term Novelty-based Exploration
9. ICML 2024A Contextual Combinatorial Bandit Approach to Negotiation
10. ICML 2024Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models
11. ICML 2024BAGEL: Bootstrapping Agents by Guiding Exploration with Language
12. ICML 2024Bayesian Exploration Networks
13. ICML 2024Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
14. ICML 2024Efficient Exploration for LLMs
15. ICML 2024Exploration and Anti-Exploration with Distributional Random Network Distillation
16. ICML 2024Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring
17. ICML 2024Fair Classification with Partial Feedback: An Exploration-Based Data Collection Approach
18. ICML 2024Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction
19. ICML 2024Handling Heterogeneous Curvatures in Bandit LQR Control
20. ICML 2024Imitation Learning in Discounted Linear MDPs without exploration assumptions
21. ICML 2024Online Learning with Bounded Recall
22. ICML 2024Online Resource Allocation with Non-Stationary Customers
23. ICML 2024Optimal Batched Linear Bandits
24. ICML 2024Provably Efficient Exploration in Quantum Reinforcement Learning with Logarithmic Worst-Case Regret
25. ICML 2024Provably Efficient Long-Horizon Exploration in Monte Carlo Tree Search through State Occupancy Regularization
26. ICML 2024Random Latent Exploration for Deep Reinforcement Learning
27. ICML 2024ReconBoost: Boosting Can Achieve Modality Reconcilement
28. ICML 2024Safe and Robust Subgame Exploitation in Imperfect Information Games
29. ICML 2024Safe Exploration in Dose Finding Clinical Trials with Heterogeneous Participants
30. ICML 2024Scalable Online Exploration via Coverability
31. ICML 2024Stochastic Bandits with ReLU Neural Networks
32. ICML 2024Straight-Through Meets Sparse Recovery: the Support Exploration Algorithm
33. ICML 2024Testing the Feasibility of Linear Programs with Bandit Feedback
34. NeurIPS 2024Bandits with Preference Feedback: A Stackelberg Game Perspective
35. NeurIPS 2024Beyond Optimism: Exploration With Partially Observable Rewards
36. NeurIPS 2024Code Repair with LLMs gives an Exploration-Exploitation Tradeoff
37. NeurIPS 2024Effective Exploration Based on the Structural Information Principles
38. NeurIPS 2024Exploration by Learning Diverse Skills through Successor State Representations
39. NeurIPS 2024Exploration, Exploitation, and Engagement in Multi-Armed Bandits with Abandonment
40. NeurIPS 2024First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-Offs
41. NeurIPS 2024Handling Learnwares from Heterogeneous Feature Spaces with Explicit Label Exploitation
42. NeurIPS 2024Hierarchical Uncertainty Exploration via Feedforward Posterior Trees
43. NeurIPS 2024How does Inverse RL Scale to Large State Spaces? A Provably Efficient Approach
44. NeurIPS 2024Improved Analysis for Bandit Learning in Matching Markets
45. NeurIPS 2024Improved Regret of Linear Ensemble Sampling
46. NeurIPS 2024Local Anti-Concentration Class: Logarithmic Regret for Greedy Linear Contextual Bandit
47. NeurIPS 2024Nearly Minimax Optimal Regret for Multinomial Logistic Bandit
48. NeurIPS 2024NeoRL: Efficient Exploration for Nonepisodic RL
49. NeurIPS 2024No-Regret Bandit Exploration based on Soft Tree Ensemble Model
50. NeurIPS 2024Offline Oracle-Efficient Learning for Contextual MDPs via Layerwise Exploration-Exploitation Tradeoff

常见问题

2023–2026 年四大会议一共有多少篇探索利用论文？

共 235 篇，按年份分别是 2023 年 47 篇、2024 年 63 篇、2025 年 54 篇、2026 年 71 篇。

NeurIPS 2026 有多少篇探索利用论文？

NeurIPS 2026 有 25 篇探索利用论文，上一届是 20 篇。

ICLR 2026 有多少篇探索利用论文？

ICLR 2026 有 23 篇探索利用论文，上一届是 10 篇。

ICML 2026 有多少篇探索利用论文？

ICML 2026 有 19 篇探索利用论文，上一届是 21 篇。

CVPR 2026 有多少篇探索利用论文？

CVPR 2026 有 4 篇探索利用论文，上一届是 3 篇。

哪个会议的探索利用论文最多？

NeurIPS，2023–2026 年共 93 篇。