Monte Carlo Tree Search papers, 2023–2026

Key findings

• Monte Carlo Tree Search went from 115 papers in 2023 to 278 in 2026, roughly 2.4x in three years.
• NeurIPS publishes the most Monte Carlo Tree Search work: 302 papers from 2023 to 2026, 39% of the four-venue total.
• The fastest-growing overlap is with AI Agents: papers tagged with both rose from 1 in 2023 to 26 in 2026.
• Among the 5 topics under Games and Planning, it ranks #3 by 2026 paper count; the fastest grower in the group, Classical Planning, is up 3.3x versus 2.4x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Monte Carlo Tree Search papers

100 papers, page 2 of 2

51. NeurIPS 2025Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems
52. NeurIPS 2025Per-Architecture Training-Free Metric Optimization for Neural Architecture Search
53. NeurIPS 2025Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach
54. NeurIPS 2025PINNs with Learnable Quadrature
55. NeurIPS 2025PlanU: Large Language Model Reasoning through Planning under Uncertainty
56. NeurIPS 2025Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
57. NeurIPS 2025Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs
58. NeurIPS 2025ProtInvTree: Deliberate Protein Inverse Folding with Reward-guided Tree Search
59. NeurIPS 2025Quantum speedup of non-linear Monte Carlo problems
60. NeurIPS 2025Random Search Neural Networks for Efficient and Expressive Graph Learning
61. NeurIPS 2025Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
62. NeurIPS 2025Results of the Big ANN: NeurIPS’23 competition
63. NeurIPS 2025Retrosynthesis Planning via Worst-path Policy Optimisation in Tree-structured MDPs
64. NeurIPS 2025Reverse Diffusion Sequential Monte Carlo Samplers
65. NeurIPS 2025Reverse-Annealed Sequential Monte Carlo for Efficient Bayesian Optimal Experiment Design
66. NeurIPS 2025RF-Agent: Automated Reward Function Design via Language Agent Tree Search
67. NeurIPS 2025Robust Contextual Pricing
68. NeurIPS 2025Rollout Roulette: A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods
69. NeurIPS 2025SCAN: Self-Denoising Monte Carlo Annotation for Robust Process Reward Learning
70. NeurIPS 2025Schrödinger Bridge Matching for Tree-Structured Costs and Entropic Wasserstein Barycentres
71. NeurIPS 2025SEEA-R1: Tree-Structured Reinforcement Fine-Tuning for Self-Evolving Embodied Agents
72. NeurIPS 2025Sequential Monte Carlo for Policy Optimization in Continuous POMDPs
73. NeurIPS 2025SIGMA: Refining Large Language Model Reasoning via Sibling-Guided Monte Carlo Augmentation
74. NeurIPS 2025SolverLLM: Leveraging Test-Time Scaling for Optimization Problem via LLM-Guided Search
75. NeurIPS 2025SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement
76. NeurIPS 2025STree: Speculative Tree Decoding for Hybrid State Space Models
77. NeurIPS 2025Structural Entropy Guided Agent for Detecting and Repairing Knowledge Deficiencies in LLMs
78. NeurIPS 2025SYMPHONY: Synergistic Multi-agent Planning with Heterogeneous Language Model Assembly
79. NeurIPS 2025T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning
80. NeurIPS 2025TensorRL-QAS: Reinforcement learning with tensor networks for improved quantum architecture search
81. NeurIPS 2025Test Time Scaling for Neural Processes
82. NeurIPS 2025Test-Time Scaling of Diffusion Models via Noise Trajectory Search
83. NeurIPS 2025TF-MAS: Training-free Mamba2 Architecture Search
84. NeurIPS 2025The Complexity of Finding Local Optima in Contrastive Learning
85. NeurIPS 2025Train on Pins and Test on Obstacles for Rectilinear Steiner Minimum Tree
86. NeurIPS 2025Training-Free Guidance Beyond Differentiability: Scalable Path Steering with Tree Search in Diffusion and Flow Models
87. NeurIPS 2025Traversal Verification for Speculative Tree Decoding
88. NeurIPS 2025Tree Ensemble Explainability through the Hoeffding Functional Decomposition and TreeHFD Algorithm
89. NeurIPS 2025Tree of Preferences for Diversified Recommendation
90. NeurIPS 2025Tree-Based Premise Selection for Lean4
91. NeurIPS 2025Tree-Sliced Entropy Partial Transport
92. NeurIPS 2025TreeFinder: A US-Scale Benchmark Dataset for Individual Tree Mortality Monitoring Using High-Resolution Aerial Imagery
93. NeurIPS 2025TreeSplat: Mergeable Tree for Deformable Gaussian Splatting
94. NeurIPS 2025TreeSynth: Synthesizing Diverse Data from Scratch via Tree-Guided Subspace Partitioning
95. NeurIPS 2025Tru-POMDP: Task Planning Under Uncertainty via Tree of Hypotheses and Open-Ended POMDPs
96. NeurIPS 2025Uncertainty-Guided Exploration for Efficient AlphaZero Training
97. NeurIPS 2025Variational Polya Tree
98. NeurIPS 2025We Should Chart an Atlas of All the World's Models
99. NeurIPS 2025Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search
100. NeurIPS 2025Yggdrasil: Bridging Dynamic Speculation and Static Runtime for Latency-Optimal Tree-Based LLM Decoding

FAQ

How many Monte Carlo Tree Search papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

773 in total: 115 in 2023, 144 in 2024, 236 in 2025, 278 in 2026.

How many Monte Carlo Tree Search papers are at NeurIPS 2026?

NeurIPS 2026 has 99 Monte Carlo Tree Search papers, versus 100 the year before.

How many Monte Carlo Tree Search papers are at ICLR 2026?

ICLR 2026 has 60 Monte Carlo Tree Search papers, versus 49 the year before.

How many Monte Carlo Tree Search papers are at ICML 2026?

ICML 2026 has 105 Monte Carlo Tree Search papers, versus 75 the year before.

How many Monte Carlo Tree Search papers are at CVPR 2026?

CVPR 2026 has 14 Monte Carlo Tree Search papers, versus 12 the year before.

Which conference publishes the most Monte Carlo Tree Search papers?

NeurIPS, with 302 papers from 2023 to 2026.