通用机器学习 · unsupervised and semisupervised learning论文趋势 2023–2026
通用机器学习：unsupervised_and_semisupervised_learning
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 2,683 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 318 | 87 | 157 | 87 | 649 |
| 2024 | 118 | 236 | 115 | 84 | 553 |
| 2025 | 203 | 174 | 239 | 66 | 682 |
| 2026 | 194 | 187 | 348 | 70 | 799 |
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 348 篇，第 7 / 7 页
- ICML 2026Thoughtbubbles: an Unsupervised Method for Parallel Thinking in Latent Space
- ICML 2026TimeLAVA: Learning-Agnostic Valuation for Time Series Data
- ICML 2026ToaSt: Token Channel Selection and Structured Pruning for Efficient ViT
- ICML 2026Toward Scalable and Valid Conditional Independence Testing with Spectral Representations
- ICML 2026Toward Structural Multimodal Representations: Specialization, Selection, and Sparsification via Mixture-of-Experts
- ICML 2026Towards One-for-All Anomaly Detection for Tabular Data
- ICML 2026Towards Uniformity and Alignment for Multimodal Representation Learning
- ICML 2026Tracing the Persona Circuit: How Large Language Models Encode and Express Character Traits
- ICML 2026Trajectory-Aware Certified Decentralized Unlearning via SGD Stability
- ICML 2026Transfer Learning in High-dimensional Ising Models
- ICML 2026Transfer Learning in Nonparametric Regression with Deep ReLU Networks
- ICML 2026Transformer Circuits Can Realize Clustering Algorithms
- ICML 2026Transport Clustering: Solving Low-Rank Optimal Transport via Clustering
- ICML 2026Transporting Task Vectors across Different Architectures without Training
- ICML 2026Tree-Structured Orthonormal Decomposition of the Aitchison Simplex
- ICML 2026TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
- ICML 2026TuneAhead: Predicting Fine-tuning Performance Before Training Begins
- ICML 2026Tuning-Free One-Class Discriminant Learning for Tabular Anomaly Detection
- ICML 2026Two-Layer Linear Auto-Regressive Models Estimate Latent States
- ICML 2026Two-Stage Unit Tying for Simplifying Differentiable Logic Gate Networks
- ICML 2026Uncovering Bias Mechanisms in Observational Studies
- ICML 2026Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference
- ICML 2026Understanding the Gaps in Satisficing Bandits
- ICML 2026Understanding Transfer Learning of RNA Foundation Models on Downstream Tasks
- ICML 2026Unfolded Laplacian Spectral Embedding: A Theoretically Grounded Approach to Dynamic Network Representation
- ICML 2026UniFast-HGR: Scalable and Efficient Maximal Correlation for Multimodal Models
- ICML 2026Unifying and Optimizing Data Values for Selection via Sequential Decision-Making
- ICML 2026Unifying Stacking and Cascading for Efficient Ensemble Inference
- ICML 2026Universal Algorithm-Implicit Learning
- ICML 2026Universal Representation of Generalized Convex Functions and their Gradients
- ICML 2026Unlocking the Potential of Continual Model Merging: An ODE Perspective
- ICML 2026Unsupervised Camouflaged Object Detection with Dual-Eigenvector Spectral Pseudo-Labeling and Contrastive Refinement
- ICML 2026Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
- ICML 2026Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability
- ICML 2026Unsupervised Hierarchical Skill Discovery
- ICML 2026Unsupervised Neural Langevin Sampler for Mixed Integer Linear Programming
- ICML 2026Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
- ICML 2026Unsupervised Process-Aware Coreset Selection for In-Context Learning
- ICML 2026Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking
- ICML 2026Unveiling And Addressing Dimensional Collapse In Vector Quantization Models Via Codebook Regularization
- ICML 2026Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization
- ICML 2026USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning
- ICML 2026Variational Entropic Optimal Transport
- ICML 2026Von Mises-Fisher Mixture Model with Dynamic Shrinkage for Realistic Test-Time Transduction
- ICML 2026What Language is This? Ask Your Tokenizer.
- ICML 2026What Linear Probes Miss: Multi-View Probing for Weight-Space Learning
- ICML 2026When Generalized Zero-Shot Learning Meets PU Learning: A Plug-and-Play Framework for Seen-Class Bias Mitigation
- ICML 2026WorldComp2D: Spatio-semantic Representations of Object Identity and Location from Local Views
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查通用机器学习 · unsupervised and semisupervised learning在 ICML 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "gml-unsupervised-and-semisupervised-learning"}
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。