通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026

主要结论

• 通用机器学习 · unsupervised and semisupervised learning论文从 2023 年的 649 篇增长到 2026 年的 799 篇，三年间扩大到约 1.2 倍。
• ICML 是发通用机器学习 · unsupervised and semisupervised learning论文最多的会议，2023–2026 年共 859 篇，占四个会议总量的 32%。
• 交叉方向里涨得最快的是深度学习 · self supervised learning：同时属于两个主题的论文从 2023 年的 23 篇增至 2026 年的 86 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 1；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · unsupervised and semisupervised learning是 1.2 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 general kernel framework for non-CND distance measures using $|\mathcal{D}|$-dimensional sparse landmark embeddings
• ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
• ICLR 2026A Generalized Geometric Theoretical Framework of Centroid Discriminant Analysis for Linear Classification of Multi-dimensional Data
• CVPR 2026COG Confidence-aware Optimal Geometric Correspondence for Unsupervised Single-reference Novel Object
• NeurIPS 2025$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
• ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
• ICLR 2025A General Framework for Producing Interpretable Semantic Text Embeddings
• CVPR 2025A General Adaptive Dual-level Weighting Mechanism for Remote Sensing Pansharpening
• NeurIPS 2024GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
• ICML 2024CKGConv: General Graph Convolution with Continuous Kernels
• ICLR 2024A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks
• CVPR 2024Dual Prototype Attention for Unsupervised Video Object Segmentation
• NeurIPS 2023$H$-Consistency Bounds: Characterization and Extensions
• ICML 2023A Mathematical Model for Curriculum Learning for Parities
• ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
• CVPR 2023A General Regret Bound of Preconditioned Gradient Method for DNN Training
• NeurIPS 2026Attention-based PCA
• ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
• ICLR 2026A Single Architecture for Representing Invariance Under Any Space Group
• CVPR 2026CROWn A Unified Framework for Anti-Aliased Downsampling and Phase-Calibrated Fusion

全部通用机器学习 · unsupervised and semisupervised learning论文

共 187 篇，第 3 / 4 页

101. ICLR 2026Learning Admissible Heuristics for A*: Theory and Practice
102. ICLR 2026Learning from Label Proportions via Proportional Value Classification
103. ICLR 2026Learning Pseudorandom Numbers with Transformers: Permuted Congruential Generators, Curricula, and Interpretability
104. ICLR 2026Learning Robust Intervention Representations with Delta Embeddings
105. ICLR 2026Learning to Be Uncertain: Pre-training World Models with Horizon-Calibrated Uncertainty
106. ICLR 2026Let OOD Feature Exploring Vast Predefined Classifiers
107. ICLR 2026LLM DNA: Tracing Model Evolution via Functional Representations
108. ICLR 2026LLMs Process Lists With General Filter Heads
109. ICLR 2026Lookup multivariate Kolmogorov-Arnold Networks
110. ICLR 2026Maximizing Asynchronicity in Event-based Neural Networks
111. ICLR 2026Maximizing Incremental Information Entropy for Contrastive Learning
112. ICLR 2026Measuring the Intrinsic Dimension of Earth Representations
113. ICLR 2026Mechanistic Independence: A Principle for Identifiable Disentangled Representations
114. ICLR 2026Mini-cluster Guided Long-tailed Deep Clustering
115. ICLR 2026Mitigating Spurious Correlation via Distributionally Robust Learning with Hierarchical Ambiguity Sets
116. ICLR 2026Modeling the Density of Pixel-level Self-supervised Embeddings for Unsupervised Pathology Segmentation in Medical CT
117. ICLR 2026Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows
118. ICLR 2026Multimodal Classification via Total Correlation Maximization
119. ICLR 2026NAB: Neural Adaptive Binning for Sparse-View CT reconstruction
120. ICLR 2026Navigating the Latent Space Dynamics of Neural Models
121. ICLR 2026Neural Sum-of-Squares: Certifying the Nonnegativity of Polynomials with Transformers
122. ICLR 2026Non-Clashing Teaching in Graphs: Algorithms, Complexity, and Bounds
123. ICLR 2026On the Alignment Between Supervised and Self-Supervised Contrastive Learning
124. ICLR 2026On the Lipschitz Continuity of Set Aggregation Functions and Neural Networks for Sets
125. ICLR 2026On the Predictive Power of Representation Dispersion in Language Models
126. ICLR 2026On the Universality and Complexity of GNN for Solving Second-order Cone Programs
127. ICLR 2026On the Wasserstein Geodesic Principal Component Analysis of probability measures
128. ICLR 2026Optimal Brain Restoration for Joint Quantization and Sparsification of LLMs
129. ICLR 2026OrthoRF: Exploring Orthogonality in Object-Centric Representations
130. ICLR 2026PHyCLIP: $\ell_1$-Product of Hyperbolic Factors Unifies Hierarchy and Compositionality in Vision-Language Representation Learning
131. ICLR 2026Poly-attention: a general scheme for higher-order self-attention
132. ICLR 2026Polynomial, trigonometric, and tropical activations
133. ICLR 2026Pose Prior Learner: Unsupervised Categorical Prior Learning for Pose Estimation
134. ICLR 2026PredNext: Explicit Cross-View Temporal Prediction for Unsupervised Learning in Spiking Neural Networks
135. ICLR 2026Preventing Model Collapse Under Overparametrization: Optimal Mixing Ratios for Interpolation Learning and Ridge Regression
136. ICLR 2026PRISM: Partial-label Relational Inference with Spatial and Spectral Cues
137. ICLR 2026Probing in the Dark: State Entropy Maximization for POMDPs
138. ICLR 2026Pseudo-Non-Linear Data Augmentation: A Constrained Energy Minimization Viewpoint
139. ICLR 2026PU-BENCH: A UNIFIED BENCHMARK FOR RIGOROUS AND REPRODUCIBLE PU LEARNING
140. ICLR 2026Rectified Decoupled Dataset Distillation: A Closer Look for Fair and Comprehensive Evaluation
141. ICLR 2026Reducing Class-Wise Performance Disparity via Margin Regularization
142. ICLR 2026Resurfacing the Instance-only Dependent Label Noise Model through Loss Correction
143. ICLR 2026Rethinking Consistent Multi-Label Classification under Inexact Supervision
144. ICLR 2026Rethinking Unsupervised Cross-modal Flow Estimation: Learning from Decoupled Optimization and Consistency Constraint
145. ICLR 2026Revela: Dense Retriever Learning via Language Modeling
146. ICLR 2026Revisiting [CLS] and Patch Token Interaction in Vision Transformers
147. ICLR 2026Robustify Spiking Neural Networks via Dominant Singular Deflation under Heterogeneous Training Vulnerability
148. ICLR 2026Sample Lottery: Unsupervised Discovery of Critical Instances for LLM Reasoning
149. ICLR 2026Samples Are Not Equal: A Sample Selection Approach for Deep Clustering
150. ICLR 2026Selective Rotary Position Embedding

常见问题

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

共 2,683 篇，按年份分别是 2023 年 649 篇、2024 年 553 篇、2025 年 682 篇、2026 年 799 篇。

NeurIPS 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

NeurIPS 2026 有 194 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 203 篇。

ICLR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

ICLR 2026 有 187 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 174 篇。

ICML 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

ICML 2026 有 348 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 239 篇。

CVPR 2026 有多少篇通用机器学习 · unsupervised and semisupervised learning论文？

CVPR 2026 有 70 篇通用机器学习 · unsupervised and semisupervised learning论文，上一届是 66 篇。

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

ICML，2023–2026 年共 859 篇。