探索利用论文趋势 2023–2026
Bandit 在线学习
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 235 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 18 | 9 | 19 | 1 | 47 |
| 2024 | 30 | 6 | 25 | 2 | 63 |
| 2025 | 20 | 10 | 21 | 3 | 54 |
| 2026 | 25 | 23 | 19 | 4 | 71 |
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 235 篇,第 1 / 5 页
- CVPR 2026DreamSAC Learning Hamiltonian World Models via Symmetry Exploration
- CVPR 2026From Exploration to Exploitation A Two-Stage Entropy RLVR Approach for
- CVPR 2026ReLaX Reasoning with Latent Exploration for Large Reasoning Models
- CVPR 2026Underground Plant Exploration Non-Destructive 3D Root Assessment with GPR Based
- ICLR 2026Beyond Noisy-TVs: Noise-Robust Exploration Via Learning Progress Monitoring
- ICLR 2026Contextual Similarity Distillation: Ensemble Uncertainties with a Single Model
- ICLR 2026Controllable Exploration in Hybrid-Policy RLVR for Multi-Modal Reasoning
- ICLR 2026Demystifying Emergent Exploration in Goal-Conditioned RL
- ICLR 2026Discovering Diverse Behaviors via Temporal Contrastive Learning
- ICLR 2026DIVERSE: Disagreement-Inducing Vector Evolution for Rashomon Set Exploration
- ICLR 2026EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget
- ICLR 2026Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward
- ICLR 2026Flow Expansion via Verifier-Constrained Noised State Space Exploration
- ICLR 2026In-Context Learning for Pure Exploration
- ICLR 2026Instance-Dependent Fixed-Budget Pure Exploration in Reinforcement Learning
- ICLR 2026Is Pure Exploitation Sufficient in Exogenous MDPs with Linear Function Approximation?
- ICLR 2026Laplacian Kernelized Bandit
- ICLR 2026Learn the Ropes, Then Trust the Wins: Self-imitation with Progressive Exploration for Agentic Reinforcement Learning
- ICLR 2026Multi-Armed Bandits with Minimum Aggregated Revenue Constraints
- ICLR 2026Next-ToBE: Probabilistic Next Token-Bag Exploitation for Activating Anticipatory Capacity in LLMs
- ICLR 2026Non-Asymptotic Analysis of (Sticky) Track-and-Stop
- ICLR 2026Risk-Sensitive Reinforcement Learning for Alleviating Exploration Dilemmas in Large Language Models
- ICLR 2026Sample-efficient and Scalable Exploration in Continuous-Time RL
- ICLR 2026Strategic Scaling of Test-Time Compute: A Bandit Learning Approach
- ICLR 2026Token Hidden Reward: Steering Exploration-Exploitation in Group Relative Deep Reinforcement Learning
- ICLR 2026Universal Value-Function Uncertainties
- ICLR 2026When Greedy Wins: Emergent Exploitation Bias in Meta-Bandit LLM Training
- ICML 2026Bandit Social Leaning Dynamics with Exploration Episodes
- ICML 2026Bilinear Bandits with Partially Observable Features
- ICML 2026Covariance Volume Maximization for Embodied Latent Exploration in Deep Reinforcement Learning
- ICML 2026Creat3r: Confidence Reaggregation for Exploration-aware Active 3D Reconstruction
- ICML 2026CUPID in the Model Zoo: Online Matchmaking for Selecting Your Dream LLM
- ICML 2026Data-Source Adaptive Online Learning under Heteroscedastic Noise
- ICML 2026DecFus: Decentralized Layer-wise Fusion with Dynamic Exploration and Exploitation
- ICML 2026DF-ExpEnse: Diffusion Filtered Exploration for Sample Efficient Finetuning
- ICML 2026Exploration-free Algorithms for Multi-group Mean Estimation
- ICML 2026Follow-the-Perturbed-Leader for Decoupled Bandits: Best-of-Both-Worlds and Practicality
- ICML 2026From Bits to Rounds: Parallel Decoding with Exploration for Diffusion Language Models
- ICML 2026HyPER: Bridging Exploration and Exploitation for Scalable LLM Reasoning with Hypothesis Path Expansion and Reduction
- ICML 2026Improved Bounds for Reward-Agnostic and Reward-Free Exploration
- ICML 2026Incentivized Exploration with Stochastic Covariates: A Two-Stage Mechanism Design for Recommender System
- ICML 2026Long Live The Balance: Information Bottleneck Driven Tree-based Policy Optimization
- ICML 2026OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
- ICML 2026Optimal Top-$k$ Identification from Pairwise Comparisons
- ICML 2026Tracking Drift: Variation-Aware Entropy Scheduling for Non-Stationary Reinforcement Learning
- ICML 2026XRPO: Pushing the Limits of GRPO with Targeted Exploration and Exploitation
- NeurIPS 2026Agnostic Online Learning with Reliable Abstention
- NeurIPS 2026Boosting Inference with Guided Reasoning: Stochastic Exploration for Recursive Models
- NeurIPS 2026CIG: Exploration via Conditional Information Gain
- NeurIPS 2026Contrastive Pretraining Scales Agentic Exploration
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查探索利用在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "exploration-exploitation"}
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。