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

348 papers, page 5 of 7

201. ICML 2026nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
202. ICML 2026Near-Optimal Regret for Policy Optimization in Contextual MDPs with General Offline Function Approximation
203. ICML 2026Negatives-Dominant Contrastive Learning for Generalization in Imbalanced Domains
204. ICML 2026NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
205. ICML 2026New Algorithms for Fully-Dynamic k-center with Outliers
206. ICML 2026Newton-coupled Dual-Teacher Semi-supervised Learning Framework
207. ICML 2026Noise-Robust Density Estimation for Tabular Data Anomaly Detection
208. ICML 2026Nonlinear Covariate Balance in Experimental Design
209. ICML 2026Not All Prefills Are Equal: PPD Disaggregation for Multi-turn LLM Serving
210. ICML 2026Omitted Variable Bias in Language Models Under Distribution Shift
211. ICML 2026On Contraction of Sequential and Offset Rademacher Complexities
212. ICML 2026On Learnability and Disambiguation of Multiclass Partial Concept Classes
213. ICML 2026On Testing Conditional Mean Independence for Manifold-Valued Data
214. ICML 2026On the Difficulty of Learning a Meta-network for Training Data Selection
215. ICML 2026On the Interaction of Batch Noise, Adaptivity, and Compression, under $(L_0,L_1)$-Smoothness: An SDE Approach
216. ICML 2026On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective
217. ICML 2026On the Plasticity and Stability for Post-Training Large Language Models
218. ICML 2026On the Power of Statistics in Class-Incremental Learning with Pretrained Models
219. ICML 2026One Batch Is Enough: A Unified Dataset Condensation Framework for General Time Series Analysis
220. ICML 2026One Coin Has Two Sides: Single Poistive Multi Label Learning from Salient Annotations
221. ICML 2026One-shot Conditional Sampling: MMD meets Nearest Neighbors
222. ICML 2026Online Learning and Inference for Cox Proportional Hazards Model Using Renewable Sieve Estimation
223. ICML 2026OPIC: Enhancing Language Model Merging via Optimizing In-Context Capability
224. ICML 2026Optimal Learning from Label Proportions with General Loss Functions
225. ICML 2026Optimal structure learning and conditional independence testing
226. ICML 2026Optimal Top-$k$ Identification from Pairwise Comparisons
227. ICML 2026Optimal Unconstrained Self-Distillation in Ridge Regression: Strict Improvements, Precise Asymptotics, and One-Shot Tuning
228. ICML 2026OPTION: Optimal Transport–Guided Flow Matching for Incomplete and Unaligned Multi-View Clustering
229. ICML 2026Orthogonal Model Merging
230. ICML 2026OvisOCR: End-to-End Document Parsing via Aligning Specialized Perception with General Reasoning
231. ICML 2026PACE: Parameter Change for Unsupervised Environment Design
232. ICML 2026PartCo: Part-Level Correspondence Priors Enhance Category Discovery
233. ICML 2026Partial Fusion of Neural Networks: Efficient Tradeoffs Between Ensembles and Weight Aggregation
234. ICML 2026Partial Identification under High-Dimensional Potential Outcomes and Confounders via Optimal Transport
235. ICML 2026PipeSD: An Efficient Cloud-Edge Collaborative Pipeline Inference Framework with Speculative Decoding
236. ICML 2026Positive-Unlabeled Learning with Extreme Scarcity of Labeled Positives
237. ICML 2026PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
238. ICML 2026Powerful and Theoretically Guaranteed Independence Testing on Heterogeneous Federated Clients
239. ICML 2026Predictive variational inference: Learn the predictively optimal posterior distribution
240. ICML 2026Prior Diffusiveness and Regret in the Linear-Gaussian Bandit
241. ICML 2026PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning
242. ICML 2026Quadratically Regularized Optimal Transport: Localization Bounds and Affine Case Analysis
243. ICML 2026Quantifying Frontier LLM Capabilities for Container Sandbox Escape
244. ICML 2026Quantitative Estimation of Target Task Performance from Unsupervised Pretext Task in Semi/Self-Supervised Learning
245. ICML 2026Rank-guided Diffusion for Noise Few-Shot Learning
246. ICML 2026Real-World Unsupervised Models Generalize to Predict Brain Responses to Out-of-Distribution Stimuli
247. ICML 2026Realizable Bayes-Consistency for General Metric Losses
248. ICML 2026Refining Context-Entangled Content Segmentation via Curriculum Selection and Anti-Curriculum Promotion
249. ICML 2026Refining Dual Spectral Sparsity in Transformed Tensor Singular Values
250. ICML 2026Relevance-Based Embeddings: Lightweight Candidate Retrieval via Heavy-Ranker Calls

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.