采样方法论文趋势 2023–2026

主要结论

• 采样方法论文从 2023 年的 122 篇增长到 2026 年的 195 篇，三年间扩大到约 1.6 倍。
• NeurIPS 是发采样方法论文最多的会议，2023–2026 年共 221 篇，占四个会议总量的 35%。
• 交叉方向里涨得最快的是MCTS：同时属于两个主题的论文从 2023 年的 4 篇增至 2026 年的 31 篇。
• 在「概率与贝叶斯」的 5 个主题里，它的 2026 年论文数排第 2；同组增长最快的高斯过程是 2.2 倍，采样方法是 1.6 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 Model of Diverse Sampling from Language Models
• ICML 2026BFTS: Thompson Sampling with Bayesian Additive Regression Trees
• ICLR 2026Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling
• CVPR 2026Active Inference for Micro-Gesture Recognition EFE-Guided Temporal Sampling and Adaptive
• NeurIPS 2025Antidistillation Sampling
• ICML 2025Connecting Thompson Sampling and UCB: Towards More Efficient Trade-offs Between Privacy and Regret
• ICLR 2025Bridging the Gap between Variational Inference and Stochastic Gradient MCMC in Function Space
• CVPR 2025AutoLUT: LUT-Based Image Super-Resolution with Automatic Sampling and Adaptive Residual Learning
• NeurIPS 2024In-and-Out: Algorithmic Diffusion for Sampling Convex Bodies
• ICML 2024Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
• ICLR 2024Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
• CVPR 2024G-FARS: Gradient-Field-based Auto-Regressive Sampling for 3D Part Grouping
• NeurIPS 2023A Dynamical System View of Langevin-Based Non-Convex Sampling
• ICML 2023Adaptive Annealed Importance Sampling with Constant Rate Progress
• ICLR 2023Any-scale Balanced Samplers for Discrete Space
• CVPR 2023Change-Aware Sampling and Contrastive Learning for Satellite Images
• NeurIPS 2026A Semantic-Sampling Framework for Evaluating Calibration in Open-Ended Question Answering
• ICML 2026Box Thirding: Anytime Best Arm Identification under Insufficient Sampling
• ICLR 2026On Coreset for LASSO Regression Problem with Sensitivity Sampling
• CVPR 2026Designing Instance-Level Sampling Schedules via REINFORCE with James-Stein Shrinkage

全部采样方法论文

共 167 篇，第 3 / 4 页

101. NeurIPS 2025$\Psi$-Sampler: Initial Particle Sampling for SMC-Based Inference-Time Reward Alignment in Score Models
102. NeurIPS 2025A Black-Box Debiasing Framework for Conditional Sampling
103. NeurIPS 2025Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking
104. NeurIPS 2025Accelerating data-driven algorithm selection for combinatorial partitioning problems
105. NeurIPS 2025AdaptGrad: Adaptive Sampling to Reduce Noise
106. NeurIPS 2025Adaptive Stochastic Coefficients for Accelerating Diffusion Sampling
107. NeurIPS 2025Amortized Sampling with Transferable Normalizing Flows
108. NeurIPS 2025Antidistillation Sampling
109. NeurIPS 2025Breaking AR’s Sampling Bottleneck: Provable Acceleration via Diffusion Language Models
110. NeurIPS 2025CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation
111. NeurIPS 2025Channel Simulation and Distributed Compression with Ensemble Rejection Sampling
112. NeurIPS 2025Consistency of the $k_n$-nearest neighbor rule under adaptive sampling
113. NeurIPS 2025Constrained Linear Thompson Sampling
114. NeurIPS 2025Constrained Sampling for Language Models Should Be Easy: An MCMC Perspective
115. NeurIPS 2025Convex Potential Mirror Langevin Algorithm for Efficient Sampling of Energy-Based Models
116. NeurIPS 2025Corrector Sampling in Language Models
117. NeurIPS 2025Coupled Data and Measurement Space Dynamics for Enhanced Diffusion Posterior Sampling
118. NeurIPS 2025Cross-fluctuation phase transitions reveal sampling dynamics in diffusion models
119. NeurIPS 2025DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restoration
120. NeurIPS 2025Discrete Neural Flow Samplers with Locally Equivariant Transformer
121. NeurIPS 2025Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation
122. NeurIPS 2025Efficient Multi-bit Quantization Network Training via Weight Bias Correction and Bit-wise Coreset Sampling
123. NeurIPS 2025Efficient semantic uncertainty quantification in language models via diversity-steered sampling
124. NeurIPS 2025Enhancing the Outcome Reward-based RL Training of MLLMs with Self-Consistency Sampling
125. NeurIPS 2025Exploration via Feature Perturbation in Contextual Bandits
126. NeurIPS 2025Fast constrained sampling in pre-trained diffusion models
127. NeurIPS 2025Fast Local Search Algorithms for Clustering with Adaptive Sampling and Bandit Strategies
128. NeurIPS 2025Fast Non-Log-Concave Sampling under Nonconvex Equality and Inequality Constraints with Landing
129. NeurIPS 2025FedRTS: Federated Robust Pruning via Combinatorial Thompson Sampling
130. NeurIPS 2025Feel-Good Thompson Sampling for Contextual Bandits: a Markov Chain Monte Carlo Showdown
131. NeurIPS 2025From stability of Langevin diffusion to convergence of proximal MCMC for non-log-concave sampling
132. NeurIPS 2025GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility
133. NeurIPS 2025GOOD: Training-Free Guided Diffusion Sampling for Out-of-Distribution Detection
134. NeurIPS 2025Learnable Sampler Distillation for Discrete Diffusion Models
135. NeurIPS 2025Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models
136. NeurIPS 2025Masked Diffusion Models as Energy Minimization
137. NeurIPS 2025Metropolis Adjusted Microcanonical Hamiltonian Monte Carlo
138. NeurIPS 2025Metropolis-Hastings Sampling for 3D Gaussian Reconstruction
139. NeurIPS 2025MISA: Memory-Efficient LLMs Optimization with Module-wise Importance Sampling
140. NeurIPS 2025Mitigating Instability in High Residual Adaptive Sampling for PINNs via Langevin Dynamics
141. NeurIPS 2025No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
142. NeurIPS 2025Parallelizing MCMC Across the Sequence Length
143. NeurIPS 2025PID-controlled Langevin Dynamics for Faster Sampling on Generative Models
144. NeurIPS 2025Posterior Sampling by Combining Diffusion Models with Annealed Langevin Dynamics
145. NeurIPS 2025Riemannian Proximal Sampler for High-accuracy Sampling on Manifolds
146. NeurIPS 2025Robust Sampling for Active Statistical Inference
147. NeurIPS 2025Sample-Adaptivity Tradeoff in On-Demand Sampling
148. NeurIPS 2025Sampled Estimators For Softmax Must Be Biased
149. NeurIPS 2025Sampling 3D Molecular Conformers with Diffusion Transformers
150. NeurIPS 2025Sampling by averaging: A multiscale approach to score estimation

常见问题

2023–2026 年四大会议一共有多少篇采样方法论文？

共 640 篇，按年份分别是 2023 年 122 篇、2024 年 156 篇、2025 年 167 篇、2026 年 195 篇。

NeurIPS 2026 有多少篇采样方法论文？

NeurIPS 2026 有 64 篇采样方法论文，上一届是 67 篇。

ICLR 2026 有多少篇采样方法论文？

ICLR 2026 有 46 篇采样方法论文，上一届是 48 篇。

ICML 2026 有多少篇采样方法论文？

ICML 2026 有 71 篇采样方法论文，上一届是 36 篇。

CVPR 2026 有多少篇采样方法论文？

CVPR 2026 有 14 篇采样方法论文，上一届是 16 篇。

哪个会议的采样方法论文最多？

NeurIPS，2023–2026 年共 221 篇。