General ML · unsupervised and semisupervised learning papers, 2023–2026

Key findings

• General ML · unsupervised and semisupervised learning went from 649 papers in 2023 to 799 in 2026, roughly 1.2x in three years.
• ICML publishes the most General ML · unsupervised and semisupervised learning work: 859 papers from 2023 to 2026, 32% of the four-venue total.
• The fastest-growing overlap is with Deep learning · self supervised learning: papers tagged with both rose from 23 in 2023 to 86 in 2026.
• Among the 6 topics under General Machine Learning, it ranks #1 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 1.2x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All General ML · unsupervised and semisupervised learning papers

239 papers, page 5 of 5

201. ICML 2025TeDS: Joint Learning of Diachronic and Synchronic Perspectives in Quaternion Space for Temporal Knowledge Graph Completion
202. ICML 2025Tensor Decomposition Based Memory-Efficient Incremental Learning
203. ICML 2025The Batch Complexity of Bandit Pure Exploration
204. ICML 2025The Complexity of Learning Sparse Superposed Features with Feedback
205. ICML 2025The Noisy Laplacian: a Threshold Phenomenon for Non-Linear Dimension Reduction
206. ICML 2025The Number of Trials Matters in Infinite-Horizon General-Utility Markov Decision Processes
207. ICML 2025The Relationship Between No-Regret Learning and Online Conformal Prediction
208. ICML 2025Tight and Fast Bounds for Multi-Label Learning
209. ICML 2025Time Series Representations with Hard-Coded Invariances
210. ICML 2025TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation
211. ICML 2025To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
212. ICML 2025Towards a General Time Series Forecasting Model with Unified Representation and Adaptive Transfer
213. ICML 2025Towards an Explainable Comparison and Alignment of Feature Embeddings
214. ICML 2025Towards Lifelong Model Editing via Simulating Ideal Editor
215. ICML 2025Towards Robustness and Explainability of Automatic Algorithm Selection
216. ICML 2025Towards the Causal Complete Cause of Multi-Modal Representation Learning
217. ICML 2025Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift
218. ICML 2025Towards Understanding Parametric Generalized Category Discovery on Graphs
219. ICML 2025Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints
220. ICML 2025UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
221. ICML 2025Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
222. ICML 2025Unified K-Means Clustering with Label-Guided Manifold Learning
223. ICML 2025Universal Neural Optimal Transport
224. ICML 2025unMORE: Unsupervised Multi-Object Segmentation via Center-Boundary Reasoning
225. ICML 2025Unraveling the Interplay between Carryover Effects and Reward Autocorrelations in Switchback Experiments
226. ICML 2025Unsupervised Learning for Class Distribution Mismatch
227. ICML 2025Update Your Transformer to the Latest Release: Re-Basin of Task Vectors
228. ICML 2025Upweighting Easy Samples in Fine-Tuning Mitigates Forgetting
229. ICML 2025Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible
230. ICML 2025Vision-Language Model Selection and Reuse for Downstream Adaptation
231. ICML 2025Volume Optimality in Conformal Prediction with Structured Prediction Sets
232. ICML 2025Volume-Aware Distance for Robust Similarity Learning
233. ICML 2025Wait-Less Offline Tuning and Re-solving for Online Decision Making
234. ICML 2025Weakly Supervised Anomaly Detection via Dual-Tailed Kernel
235. ICML 2025Weakly-Supervised Contrastive Learning for Imprecise Class Labels
236. ICML 2025When Bad Data Leads to Good Models
237. ICML 2025When Data-Free Knowledge Distillation Meets Non-Transferable Teacher: Escaping Out-of-Distribution Trap is All You Need
238. ICML 2025Whoever Started the interference Should End It: Guiding Data-Free Model Merging via Task Vectors
239. ICML 2025Zero-shot Meta-learning for Tabular Prediction Tasks with Adversarially Pre-trained Transformer

FAQ

How many General ML · unsupervised and semisupervised learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

2,683 in total: 649 in 2023, 553 in 2024, 682 in 2025, 799 in 2026.

How many General ML · unsupervised and semisupervised learning papers are at NeurIPS 2026?

NeurIPS 2026 has 194 General ML · unsupervised and semisupervised learning papers, versus 203 the year before.

How many General ML · unsupervised and semisupervised learning papers are at ICLR 2026?

ICLR 2026 has 187 General ML · unsupervised and semisupervised learning papers, versus 174 the year before.

How many General ML · unsupervised and semisupervised learning papers are at ICML 2026?

ICML 2026 has 348 General ML · unsupervised and semisupervised learning papers, versus 239 the year before.

How many General ML · unsupervised and semisupervised learning papers are at CVPR 2026?

CVPR 2026 has 70 General ML · unsupervised and semisupervised learning papers, versus 66 the year before.

Which conference publishes the most General ML · unsupervised and semisupervised learning papers?

ICML, with 859 papers from 2023 to 2026.