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

318 papers, page 4 of 7

151. NeurIPS 2023Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
152. NeurIPS 2023Invariant Learning via Probability of Sufficient and Necessary Causes
153. NeurIPS 2023Inverse Reinforcement Learning with the Average Reward Criterion
154. NeurIPS 2023Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning
155. NeurIPS 2023Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition
156. NeurIPS 2023Kernelized Cumulants: Beyond Kernel Mean Embeddings
157. NeurIPS 2023KuaiSim: A Comprehensive Simulator for Recommender Systems
158. NeurIPS 2023Learning and Collusion in Multi-unit Auctions
159. NeurIPS 2023Learning and processing the ordinal information of temporal sequences in recurrent neural circuits
160. NeurIPS 2023Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation
161. NeurIPS 2023Learning Exponential Families from Truncated Samples
162. NeurIPS 2023Learning From Biased Soft Labels
163. NeurIPS 2023Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
164. NeurIPS 2023Learning Motion Refinement for Unsupervised Face Animation
165. NeurIPS 2023Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
166. NeurIPS 2023Learning to Configure Separators in Branch-and-Cut
167. NeurIPS 2023Learning to Discover Skills through Guidance
168. NeurIPS 2023Learning Universal Policies via Text-Guided Video Generation
169. NeurIPS 2023Leveraging sparse and shared feature activations for disentangled representation learning
170. NeurIPS 2023List and Certificate Complexities in Replicable Learning
171. NeurIPS 2023Lo-Hi: Practical ML Drug Discovery Benchmark
172. NeurIPS 2023Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
173. NeurIPS 2023Lovász Principle for Unsupervised Graph Representation Learning
174. NeurIPS 2023M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery
175. NeurIPS 2023Machine learning detects terminal singularities
176. NeurIPS 2023Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
177. NeurIPS 2023Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration
178. NeurIPS 2023Maximum Average Randomly Sampled: A Scale Free and Non-parametric Algorithm for Stochastic Bandits
179. NeurIPS 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
180. NeurIPS 2023Metis: Understanding and Enhancing In-Network Regular Expressions
181. NeurIPS 2023Minimum Description Length and Generalization Guarantees for Representation Learning
182. NeurIPS 2023Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
183. NeurIPS 2023MLFMF: Data Sets for Machine Learning for Mathematical Formalization
184. NeurIPS 2023MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting
185. NeurIPS 2023MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability
186. NeurIPS 2023Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM
187. NeurIPS 2023Model Shapley: Equitable Model Valuation with Black-box Access
188. NeurIPS 2023Model Sparsity Can Simplify Machine Unlearning
189. NeurIPS 2023Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation
190. NeurIPS 2023Multi-Object Representation Learning via Feature Connectivity and Object-Centric Regularization
191. NeurIPS 2023Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation
192. NeurIPS 2023Mutual Information Regularized Offline Reinforcement Learning
193. NeurIPS 2023Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
194. NeurIPS 2023Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
195. NeurIPS 2023Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
196. NeurIPS 2023Neural Modulation for Flash Memory: An Unsupervised Learning Framework for Improved Reliability
197. NeurIPS 2023NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function
198. NeurIPS 2023No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand
199. NeurIPS 2023Nonparametric Teaching for Multiple Learners
200. NeurIPS 2023OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents

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.