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 2,682 篇，第 36 / 54 页

1751. ICLR 2024SAS: Structured Activation Sparsification
1752. ICLR 2024Scalable Monotonic Neural Networks
1753. ICLR 2024Scaling Laws of RoPE-based Extrapolation
1754. ICLR 2024Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View
1755. ICLR 2024SemiReward: A General Reward Model for Semi-supervised Learning
1756. ICLR 2024Set Learning for Accurate and Calibrated Models
1757. ICLR 2024SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings
1758. ICLR 2024Simplifying Transformer Blocks
1759. ICLR 2024Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation
1760. ICLR 2024Sparse Autoencoders Find Highly Interpretable Features in Language Models
1761. ICLR 2024Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging
1762. ICLR 2024Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
1763. ICLR 2024Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
1764. ICLR 2024Spurious Feature Diversification Improves Out-of-distribution Generalization
1765. ICLR 2024Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
1766. ICLR 2024STARC: A General Framework For Quantifying Differences Between Reward Functions
1767. ICLR 2024State Representation Learning Using an Unbalanced Atlas
1768. ICLR 2024StructComp: Substituting propagation with Structural Compression in Training Graph Contrastive Learning
1769. ICLR 2024Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning
1770. ICLR 2024SWAP: Sparse Entropic Wasserstein Regression for Robust Network Pruning
1771. ICLR 2024Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching
1772. ICLR 2024Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
1773. ICLR 2024Teaching Arithmetic to Small Transformers
1774. ICLR 2024The Alignment Problem from a Deep Learning Perspective
1775. ICLR 2024The Expressive Power of Transformers with Chain of Thought
1776. ICLR 2024The mechanistic basis of data dependence and abrupt learning in an in-context classification task
1777. ICLR 2024Time-Varying Propensity Score to Bridge the Gap between the Past and Present
1778. ICLR 2024To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets
1779. ICLR 2024Topological data analysis on noisy quantum computers
1780. ICLR 2024Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization
1781. ICLR 2024Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach
1782. ICLR 2024Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
1783. ICLR 2024Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching
1784. ICLR 2024Towards Meta-Pruning via Optimal Transport
1785. ICLR 2024Transferring Learning Trajectories of Neural Networks
1786. ICLR 2024Transformer Fusion with Optimal Transport
1787. ICLR 2024Transformers can optimally learn regression mixture models
1788. ICLR 2024Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
1789. ICLR 2024Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression
1790. ICLR 2024Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
1791. ICLR 2024Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
1792. ICLR 2024UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models
1793. ICLR 2024Unsupervised Order Learning
1794. ICLR 2024Unsupervised Pretraining for Fact Verification by Language Model Distillation
1795. ICLR 2024Video Decomposition Prior: Editing Videos Layer by Layer
1796. ICLR 2024VONet: Unsupervised Video Object Learning With Parallel U-Net Attention and Object-wise Sequential VAE
1797. ICLR 2024Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning
1798. ICLR 2024What does automatic differentiation compute for neural networks?
1799. ICLR 2024When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations
1800. ICLR 2024Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs

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。