MCTS论文趋势 2023–2026

主要结论

• MCTS论文从 2023 年的 115 篇增长到 2026 年的 278 篇，三年间扩大到约 2.4 倍。
• NeurIPS 是发MCTS论文最多的会议，2023–2026 年共 302 篇，占四个会议总量的 39%。
• 交叉方向里涨得最快的是AI 智能体：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 26 篇。
• 在「博弈与规划」的 5 个主题里，它的 2026 年论文数排第 3；同组增长最快的经典规划是 3.3 倍，MCTS是 2.4 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 2026A Regularization-Based Approach to Public Belief State Search for Adversarial Games
• ICML 2026$\alpha$-PFN: Fast Entropy Search via In-Context Learning
• ICLR 2026Better Learning-Augmented Spanning Tree Algorithms via Metric Forest Completion
• CVPR 2026DRS-GUI Dynamic Region Search for Training-Free GUI Grounding
• NeurIPS 2025A Single-Swap Local Search Algorithm for k-Means of Lines
• ICML 2025Accelerating Large Language Model Reasoning via Speculative Search
• ICLR 2025Analysis of Linear Mode Connectivity via Permutation-Based Weight Matching: With Insights into Other Permutation Search Methods
• CVPR 2025DyFo: A Training-Free Dynamic Focus Visual Search for Enhancing LMMs in Fine-Grained Visual Understanding
• NeurIPS 2024Speculative Monte-Carlo Tree Search
• ICML 2024Accelerated Speculative Sampling Based on Tree Monte Carlo
• ICLR 2024Chain of Log-Concave Markov Chains
• CVPR 2024Hierarchical Correlation Clustering and Tree Preserving Embedding
• NeurIPS 2023Accelerating Monte Carlo Tree Search with Probability Tree State Abstraction
• ICML 2023A new near-linear time algorithm for k-nearest neighbor search using a compressed cover tree
• ICLR 2023A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming
• CVPR 2023Bridging Search Region Interaction With Template for RGB-T Tracking
• NeurIPS 2026A Revisit of Hamiltonian Monte Carlo Efficiency on Bayesian Neural Networks
• ICML 2026A Bi-metric Framework for Efficient Nearest Neighbor Search
• ICLR 2026Dr.LLM: Dynamic Layer Routing in LLMs
• CVPR 2026UAST Unified Active Search and Tracking for Arbitrary Targets with

全部MCTS论文

共 251 篇，第 1 / 6 页

1. ICML 2026$\alpha$-PFN: Fast Entropy Search via In-Context Learning
2. ICML 2026A Bi-metric Framework for Efficient Nearest Neighbor Search
3. ICML 2026Accelerating Langevin Monte Carlo via Efficient Stochastic Runge-Kutta Methods beyond Log-Concavity
4. ICML 2026Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo
5. ICML 2026Active Continual Learning with Metaplastic Binary Bayesian Neural Networks
6. ICML 2026Advancing SVD-based LLM Compression via Layer-Wise Error Model Search
7. ICML 2026AdverMCTS: Combating Pseudo-Correctness in Code Generation via Adversarial Monte Carlo Tree Search
8. ICML 2026AI Engram: In Search of Memory Traces in Artificial Intelligence
9. ICML 2026Aligning Tree-Search Policies with Fixed Token Budgets in Test-Time Scaling of LLMs
10. ICML 2026AlphaRouter: Token-level Routing Between SLM and LLM with Reinforcement Learning and Tree Search
11. ICML 2026Approximate Nearest Neighbor Search for Modern AI: A Projection-Augmented Graph Approach
12. ICML 2026AReaL-DTA: Dynamic Tree Attention for Efficient Reinforcement Learning of Large Language Models
13. ICML 2026BESPOKE: Benchmark for Search-Augmented Large Language Model Personalization via Diagnostic Feedback
14. ICML 2026Beyond Policy Training: Recursive Solution Search from Unannotated Videos
15. ICML 2026Beyond the Bellman Recursion: A Pontryagin-Guided Framework for Non-Exponential Discounting
16. ICML 2026Bridge Matching Sampler: Scalable Sampling via Generalized Fixed-Point Diffusion Matching
17. ICML 2026BVS: Bayesian Visual Search with Multimodal Large Language Model for Fine-grained Perception
18. ICML 2026Cache Coherent Resampling for Efficient Test Time Scaling in LLM Reasoning via Adaptive Sequential Monte Carlo
19. ICML 2026Can I Have Your Order? Monte-Carlo Tree Search for Slot Filling Ordering in Diffusion Language Models
20. ICML 2026Can Microcanonical Langevin Dynamics Leverage Mini-Batch Gradient Noise?
21. ICML 2026CLARITree: Cholesky and Lookahead Accelerations for Regression with Interpretable Piecewise Linear Trees
22. ICML 2026Complexity Bounds for Dirichlet Process Slice Samplers
23. ICML 2026Computationally-efficient Graph Modeling with Refined Graph Random Features
24. ICML 2026Conditional Diffusion Sampling
25. ICML 2026Constrained Adaptive Rejection Sampling
26. ICML 2026Control Consistency Losses for Diffusion Bridges
27. ICML 2026Covariance estimation using Markov chain Monte Carlo
28. ICML 2026DC-LA: Difference-of-Convex Langevin Algorithm
29. ICML 2026Decision Tree Learning on Product Spaces
30. ICML 2026DiffuReason: Enhancing Reasoning Ability for Diffusion Language Models via Monte Carlo Tree Search
31. ICML 2026Diffusion Differentiable Resampling
32. ICML 2026Dimension-Independent Convergence of Underdamped Langevin Monte Carlo in KL Divergence
33. ICML 2026Discrete Adjoint Schrödinger Bridge Sampler
34. ICML 2026DTS: Enhancing Large Reasoning Models via Decoding Tree Sketching
35. ICML 2026Efficient Learning of Deep State Space Models via Importance Smoothing
36. ICML 2026Efficient Online Variational Estimation via Monte Carlo Sampling
37. ICML 2026Efficient Stochastic Optimisation via Sequential Monte Carlo
38. ICML 2026Entropic Mirror Monte Carlo
39. ICML 2026Escaping Whack-a-Mole: Optimizing Documentation as Repo-Specific Playbooks for Coding Agents
40. ICML 2026Exact and Approximate Algorithms for Polytree Learning
41. ICML 2026Excited Pfaffians: Generalized Neural Wave Functions Across Structure and State
42. ICML 2026Flatland: The Adventures of Gradient Descent with Large Step Sizes
43. ICML 2026Forward-KL Convergence of Time-Inhomogeneous Langevin Diffusions
44. ICML 2026From Rashomon Theory to PRAXIS: Efficient Decision Tree Rashomon Sets
45. ICML 2026Generalization of Gibbs and Langevin Monte Carlo Algorithms in the Interpolation Regime
46. ICML 2026Influence-Guided Symbolic Regression: Scientific Discovery via LLM-Driven Equation Search with Granular Feedback
47. ICML 2026Initialization is Half the Battle: Generating Diverse Images from a Guidance Potential Posterior
48. ICML 2026InteractComp: Evaluating Search Agents With Ambiguous Queries
49. ICML 2026Inverting Data Transformations via Diffusion Sampling
50. ICML 2026Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo

常见问题

2023–2026 年四大会议一共有多少篇MCTS论文？

共 773 篇，按年份分别是 2023 年 115 篇、2024 年 144 篇、2025 年 236 篇、2026 年 278 篇。

NeurIPS 2026 有多少篇MCTS论文？

NeurIPS 2026 有 99 篇MCTS论文，上一届是 100 篇。

ICLR 2026 有多少篇MCTS论文？

ICLR 2026 有 60 篇MCTS论文，上一届是 49 篇。

ICML 2026 有多少篇MCTS论文？

ICML 2026 有 105 篇MCTS论文，上一届是 75 篇。

CVPR 2026 有多少篇MCTS论文？

CVPR 2026 有 14 篇MCTS论文，上一届是 12 篇。

哪个会议的MCTS论文最多？

NeurIPS，2023–2026 年共 302 篇。