通用机器学习 · supervised learning论文趋势 2023–2026

主要结论

• 通用机器学习 · supervised learning论文从 2023 年的 263 篇增长到 2026 年的 279 篇，三年间扩大到约 1.1 倍。
• NeurIPS 是发通用机器学习 · supervised learning论文最多的会议，2023–2026 年共 731 篇，占四个会议总量的 51%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 9 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 3；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · supervised learning是 1.1 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 2026AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training
• ICML 2026$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
• ICLR 2026Adaptive Concept Discovery for Interpretable Few-Shot Text Classification
• CVPR 2026Enabling Supervised Learning of Generative Signatures for Generalized AI-Generated Images
• NeurIPS 2025$\boldsymbol{\lambda}$-Orthogonality Regularization for Compatible Representation Learning
• ICML 2025Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
• ICLR 2025Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
• CVPR 2025A Unified Framework for Heterogeneous Semi-supervised Learning
• NeurIPS 2024(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
• ICML 2024A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
• ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
• CVPR 2024Efficient Hyperparameter Optimization with Adaptive Fidelity Identification
• NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
• ICML 2023A Model-free Closeness-of-influence Test for Features in Supervised Learning
• ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
• CVPR 2023Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data
• NeurIPS 2026Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
• ICML 2026Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
• ICLR 2026Buckingham $\pi$-Invariant Test‑Time Projection for Robust PDE Surrogate Modeling
• CVPR 2026HyperNAS Enhancing Architecture Representation for NAS Predictor via Hypernetwork

全部通用机器学习 · supervised learning论文

共 731 篇，第 3 / 15 页

101. NeurIPS 2025Analog Foundation Models
102. NeurIPS 2025Anchor-based Maximum Discrepancy for Relative Similarity Testing
103. NeurIPS 2025Anytime-valid, Bayes-assisted, Prediction-Powered Inference
104. NeurIPS 2025ArchPower: Dataset for Architecture-Level Power Modeling of Modern CPU Design
105. NeurIPS 2025Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning
106. NeurIPS 2025Asymptotically Stable Quaternion-valued Hopfield-structured Neural Network with Periodic Projection-based Supervised Learning Rules
107. NeurIPS 2025AutoHood3D: A Multi‑Modal Benchmark for Automotive Hood Design and Fluid–Structure Interaction
108. NeurIPS 2025Backdoor Mitigation via Invertible Pruning Masks
109. NeurIPS 2025Bayesian Optimization with Preference Exploration using a Monotonic Neural Network Ensemble
110. NeurIPS 2025Boosting Adversarial Transferability with Spatial Adversarial Alignment
111. NeurIPS 2025Breakthrough Sensor-Limited Single View: Towards Implicit Temporal Dynamics for Time Series Domain Adaptation
112. NeurIPS 2025CALM-PDE: Continuous and Adaptive Convolutions for Latent Space Modeling of Time-dependent PDEs
113. NeurIPS 2025CLEAR: Command Level Annotated Dataset for Ransomware Detection
114. NeurIPS 2025CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
115. NeurIPS 2025Coloring Learning for Heterophilic Graph Representation
116. NeurIPS 2025ComRank: Ranking Loss for Multi-Label Complementary Label Learning
117. NeurIPS 2025Confusion-Driven Self-Supervised Progressively Weighted Ensemble Learning for Non-Exemplar Class Incremental Learning
118. NeurIPS 2025Consensus-Robust Transfer Attacks via Parameter and Representation Perturbations
119. NeurIPS 2025Contrastive Self-Supervised Learning As Neural Manifold Packing
120. NeurIPS 2025Correcting misinterpretations of additive models
121. NeurIPS 2025Cost-Sensitive Freeze-thaw Bayesian Optimization for Efficient Hyperparameter Tuning
122. NeurIPS 2025CoUn: Empowering Machine Unlearning via Contrastive Learning
123. NeurIPS 2025Data-Free Model Extraction for Black-box Recommender Systems via Graph Convolutions
124. NeurIPS 2025Decompile-Bench: Million-Scale Binary-Source Function Pairs for Real-World Binary Decompilation
125. NeurIPS 2025DecompNet: Enhancing Time Series Forecasting Models with Implicit Decomposition
126. NeurIPS 2025Decoupled Entropy Minimization
127. NeurIPS 2025DeltaPhi: Physical States Residual Learning for Neural Operators in Data-Limited PDE Solving
128. NeurIPS 2025Demystifying Spectral Feature Learning for Instrumental Variable Regression
129. NeurIPS 2025Diffusion-Guided Graph Data Augmentation
130. NeurIPS 2025Disentanglement Beyond Static vs. Dynamic: A Benchmark and Evaluation Framework for Multi-Factor Sequential Representations
131. NeurIPS 2025Distributionally Robust Performative Optimization
132. NeurIPS 2025Ditch the Denoiser: Emergence of Noise Robustness in Self-Supervised Learning from Data Curriculum
133. NeurIPS 2025Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings
134. NeurIPS 2025DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge
135. NeurIPS 2025DUAL: Learning Diverse Kernels for Aggregated Two-sample and Independence Testing
136. NeurIPS 2025EddyFormer: Accelerated Neural Simulations of Three-Dimensional Turbulence at Scale
137. NeurIPS 2025Efficient Knowledge Transfer in Federated Recommendation for Joint Venture Ecosystem
138. NeurIPS 2025EngiBench: A Framework for Data-Driven Engineering Design Research
139. NeurIPS 2025Enhancing Contrastive Learning with Variable Similarity
140. NeurIPS 2025Enhancing Privacy in Multimodal Federated Learning with Information Theory
141. NeurIPS 2025ENMA: Tokenwise Autoregression for Continuous Neural PDE Operators
142. NeurIPS 2025Evaluating LLM-contaminated Crowdsourcing Data Without Ground Truth
143. NeurIPS 2025Exploring and Exploiting Model Uncertainty in Bayesian Optimization
144. NeurIPS 2025Exploring Structural Degradation in Dense Representations for Self-supervised Learning
145. NeurIPS 2025Feature Distillation is the Better Choice for Model-Heterogeneous Federated Learning
146. NeurIPS 2025FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning
147. NeurIPS 2025Flick: Empowering Federated Learning with Commonsense Knowledge
148. NeurIPS 2025Fourier Clouds: Fast Bias Correction for Imbalanced Semi-Supervised Learning
149. NeurIPS 2025From Replication to Redesign: Exploring Pairwise Comparisons for LLM-Based Peer Review
150. NeurIPS 2025From Sequence to Structure: Uncovering Substructure Reasoning in Transformers

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · supervised learning论文？

共 1,425 篇，按年份分别是 2023 年 263 篇、2024 年 511 篇、2025 年 372 篇、2026 年 279 篇。

NeurIPS 2026 有多少篇通用机器学习 · supervised learning论文？

NeurIPS 2026 有 87 篇通用机器学习 · supervised learning论文，上一届是 171 篇。

ICLR 2026 有多少篇通用机器学习 · supervised learning论文？

ICLR 2026 有 48 篇通用机器学习 · supervised learning论文，上一届是 40 篇。

ICML 2026 有多少篇通用机器学习 · supervised learning论文？

ICML 2026 有 111 篇通用机器学习 · supervised learning论文，上一届是 114 篇。

CVPR 2026 有多少篇通用机器学习 · supervised learning论文？

CVPR 2026 有 33 篇通用机器学习 · supervised learning论文，上一届是 47 篇。

哪个会议的通用机器学习 · supervised learning论文最多？

NeurIPS，2023–2026 年共 731 篇。