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 2,682 篇，第 40 / 54 页
- NeurIPS 2024GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
- NeurIPS 2024GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI
- NeurIPS 2024Graph Edit Distance with General Costs Using Neural Set Divergence
- NeurIPS 2024Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models
- NeurIPS 2024GTA: A Benchmark for General Tool Agents
- NeurIPS 2024How Does Variance Shape the Regret in Contextual Bandits?
- NeurIPS 2024Identify Then Recommend: Towards Unsupervised Group Recommendation
- NeurIPS 2024Identifying General Mechanism Shifts in Linear Causal Representations
- NeurIPS 2024Identifying Selections for Unsupervised Subtask Discovery
- NeurIPS 2024ImageNet3D: Towards General-Purpose Object-Level 3D Understanding
- NeurIPS 2024Improved Guarantees for Fully Dynamic $k$-Center Clustering with Outliers in General Metric Spaces
- NeurIPS 2024Improving Environment Novelty Quantification for Effective Unsupervised Environment Design
- NeurIPS 2024IncomeSCM: From tabular data set to time-series simulator and causal estimation benchmark
- NeurIPS 2024Injecting Undetectable Backdoors in Obfuscated Neural Networks and Language Models
- NeurIPS 2024InversionView: A General-Purpose Method for Reading Information from Neural Activations
- NeurIPS 2024IR-CM: The Fast and General-purpose Image Restoration Method Based on Consistency Model
- NeurIPS 2024Key-Grid: Unsupervised 3D Keypoints Detection using Grid Heatmap Features
- NeurIPS 2024Language Models as Zero-shot Lossless Gradient Compressors: Towards General Neural Parameter Prior Models
- NeurIPS 2024Latent Intrinsics Emerge from Training to Relight
- NeurIPS 2024Learning Commonality, Divergence and Variety for Unsupervised Visible-Infrared Person Re-identification
- NeurIPS 2024Learning General Parameterized Policies for Infinite Horizon Average Reward Constrained MDPs via Primal-Dual Policy Gradient Algorithm
- NeurIPS 2024Learning Linear Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
- NeurIPS 2024Learning Neural Contracting Dynamics: Extended Linearization and Global Guarantees
- NeurIPS 2024Learning Segmentation from Point Trajectories
- NeurIPS 2024Learning to Embed Distributions via Maximum Kernel Entropy
- NeurIPS 2024Learning Versatile Skills with Curriculum Masking
- NeurIPS 2024Leveraging Separated World Model for Exploration in Visually Distracted Environments
- NeurIPS 2024Linear Causal Bandits: Unknown Graph and Soft Interventions
- NeurIPS 2024Logical characterizations of recurrent graph neural networks with reals and floats
- NeurIPS 2024MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection
- NeurIPS 2024MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts
- NeurIPS 2024Markov Equivalence and Consistency in Differentiable Structure Learning
- NeurIPS 2024Mining and Transferring Feature-Geometry Coherence for Unsupervised Point Cloud Registration
- NeurIPS 2024Near-Optimal Distributionally Robust Reinforcement Learning with General $L_p$ Norms
- NeurIPS 2024NeuralSolver: Learning Algorithms For Consistent and Efficient Extrapolation Across General Tasks
- NeurIPS 2024No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation
- NeurIPS 2024Nonlinear dynamics of localization in neural receptive fields
- NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
- NeurIPS 2024On the Expressive Power of Tree-Structured Probabilistic Circuits
- NeurIPS 2024On the Role of Information Structure in Reinforcement Learning for Partially-Observable Sequential Teams and Games
- NeurIPS 2024Online Budgeted Matching with General Bids
- NeurIPS 2024Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift
- NeurIPS 2024Optimistic Critic Reconstruction and Constrained Fine-Tuning for General Offline-to-Online RL
- NeurIPS 2024PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning
- NeurIPS 2024Perceiving Longer Sequences With Bi-Directional Cross-Attention Transformers
- NeurIPS 2024Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis
- NeurIPS 2024Plant-and-Steal: Truthful Fair Allocations via Predictions
- NeurIPS 2024Probabilistic size-and-shape functional mixed models
- NeurIPS 2024Provably and Practically Efficient Adversarial Imitation Learning with General Function Approximation
- NeurIPS 2024Real-Time Selection Under General Constraints via Predictive Inference
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。