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

236 papers, page 4 of 5

151. NeurIPS 2025Discovering Data Structures: Nearest Neighbor Search and Beyond
152. NeurIPS 2025Discretization-free Multicalibration through Loss Minimization over Tree Ensembles
153. NeurIPS 2025Diversifying Parallel Ergodic Search: A Signature Kernel Evolution Strategy
154. NeurIPS 2025Dynamic Algorithm for Explainable $k$-medians Clustering under $\ell_p$ Norm
155. NeurIPS 2025Empowering Decision Trees via Shape Function Branching
156. NeurIPS 2025EvoLM: In Search of Lost Language Model Training Dynamics
157. NeurIPS 2025Explainably Safe Reinforcement Learning
158. NeurIPS 2025Fast attention mechanisms: a tale of parallelism
159. NeurIPS 2025Fast Monte Carlo Tree Diffusion: 100× Speedup via Parallel and Sparse Planning
160. NeurIPS 2025Faster Generic Identification in Tree-Shaped Structural Causal Models
161. NeurIPS 2025FEAT: Free energy Estimators with Adaptive Transport
162. NeurIPS 2025Feedback-Aware MCTS for Goal-Oriented Information Seeking
163. NeurIPS 2025Feel-Good Thompson Sampling for Contextual Bandits: a Markov Chain Monte Carlo Showdown
164. NeurIPS 2025Graph-based Symbolic Regression with Invariance and Constraint Encoding
165. NeurIPS 2025Improving Decision Trees through the Lens of Parameterized Local Search
166. NeurIPS 2025Improving Monte Carlo Tree Search for Symbolic Regression
167. NeurIPS 2025In Search of Adam’s Secret Sauce
168. NeurIPS 2025Jet-Nemotron: Efficient Language Model with Post Neural Architecture Search
169. NeurIPS 2025KeeA*: Epistemic Exploratory A* Search via Knowledge Calibration
170. NeurIPS 2025LaRes: Evolutionary Reinforcement Learning with LLM-based Adaptive Reward Search
171. NeurIPS 2025Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm
172. NeurIPS 2025Learning to Better Search with Language Models via Guided Reinforced Self-Training
173. NeurIPS 2025Let's Revise Step-by-Step: A Unified Local Search Framework for Code Generation with LLMs
174. NeurIPS 2025MALinZero: Efficient Low-Dimensional Search for Mastering Complex Multi-Agent Planning
175. NeurIPS 2025MDNS: Masked Diffusion Neural Sampler via Stochastic Optimal Control
176. NeurIPS 2025Metropolis Adjusted Microcanonical Hamiltonian Monte Carlo
177. NeurIPS 2025MigGPT: Harnessing Large Language Models for Automated Migration of Out-of-Tree Linux Kernel Patches Across Versions
178. NeurIPS 2025Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge
179. NeurIPS 2025MPS-Prover: Advancing Stepwise Theorem Proving by Multi-Perspective Search and Data Curation
180. NeurIPS 2025Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
181. NeurIPS 2025Multilevel neural simulation-based inference
182. NeurIPS 2025Neural Attention Search
183. NeurIPS 2025Offline Goal-conditioned Reinforcement Learning with Quasimetric Representations
184. NeurIPS 2025Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search
185. NeurIPS 2025OptiTree: Hierarchical Thoughts Generation with Tree Search for LLM Optimization Modeling
186. NeurIPS 2025Parallelizing MCMC Across the Sequence Length
187. NeurIPS 2025Pass@K Policy Optimization: Solving Harder Reinforcement Learning Problems
188. NeurIPS 2025Per-Architecture Training-Free Metric Optimization for Neural Architecture Search
189. NeurIPS 2025Personalized Safety in LLMs: A Benchmark and A Planning-Based Agent Approach
190. NeurIPS 2025PINNs with Learnable Quadrature
191. NeurIPS 2025PlanU: Large Language Model Reasoning through Planning under Uncertainty
192. NeurIPS 2025Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities
193. NeurIPS 2025Prompted Policy Search: Reinforcement Learning through Linguistic and Numerical Reasoning in LLMs
194. NeurIPS 2025ProtInvTree: Deliberate Protein Inverse Folding with Reward-guided Tree Search
195. NeurIPS 2025Quantum speedup of non-linear Monte Carlo problems
196. NeurIPS 2025Random Search Neural Networks for Efficient and Expressive Graph Learning
197. NeurIPS 2025Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
198. NeurIPS 2025Results of the Big ANN: NeurIPS’23 competition
199. NeurIPS 2025Retrosynthesis Planning via Worst-path Policy Optimisation in Tree-structured MDPs
200. NeurIPS 2025Reverse Diffusion Sequential Monte Carlo Samplers

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.