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

798 papers, page 4 of 16

151. ICLR 2026GmNet: Revisiting Gating Mechanisms From A Frequency View
152. ICLR 2026Gradient Descent with Large Step Sizes: Chaos and Fractal Convergence Region
153. ICLR 2026GTM: A General Time-series Model for Enhanced Representation Learning of Time-Series data
154. ICLR 2026Hidden Breakthroughs in Language Model Training
155. ICLR 2026Hierarchical Encoding Tree with Modality Mixup for Cross-modal Hashing
156. ICLR 2026How Far Can Unsupervised RLVR Scale LLM Training?
157. ICLR 2026Identifiability and recoverability in self-supervised models
158. ICLR 2026Improved Object-Centric Diffusion Learning with Registers and Contrastive Alignment
159. ICLR 2026Improving Set Function Approximation with Quasi-Arithmetic Neural Networks
160. ICLR 2026In Context Semi-Supervised Learning
161. ICLR 2026Incomplete Multi-View Multi-Label Classification via Shared Codebook and Fused-Teacher Self-Distillation
162. ICLR 2026InfoNCE Induces Gaussian Distribution
163. ICLR 2026Internal Evaluation of Density-Based Clusterings with Noise
164. ICLR 2026InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models
165. ICLR 2026Jacobian Aligned Random Forests
166. ICLR 2026KDP: Simplifying Representation Dynamics in Kernel Space
167. ICLR 2026KLAS: Using Similarity to Stitch Neural Networks for an Improved Accuracy-Efficiency Tradeoff
168. ICLR 2026Know When to Abstain: Optimal Selective Classification with Likelihood Ratios
169. ICLR 2026Large Language Model Compression with Global Rank and Sparsity Optimization
170. ICLR 2026Learning Admissible Heuristics for A*: Theory and Practice
171. ICLR 2026Learning from Label Proportions via Proportional Value Classification
172. ICLR 2026Learning Pseudorandom Numbers with Transformers: Permuted Congruential Generators, Curricula, and Interpretability
173. ICLR 2026Learning Robust Intervention Representations with Delta Embeddings
174. ICLR 2026Learning to Be Uncertain: Pre-training World Models with Horizon-Calibrated Uncertainty
175. ICLR 2026Let OOD Feature Exploring Vast Predefined Classifiers
176. ICLR 2026LLM DNA: Tracing Model Evolution via Functional Representations
177. ICLR 2026LLMs Process Lists With General Filter Heads
178. ICLR 2026Lookup multivariate Kolmogorov-Arnold Networks
179. ICLR 2026Maximizing Asynchronicity in Event-based Neural Networks
180. ICLR 2026Maximizing Incremental Information Entropy for Contrastive Learning
181. ICLR 2026Measuring the Intrinsic Dimension of Earth Representations
182. ICLR 2026Mechanistic Independence: A Principle for Identifiable Disentangled Representations
183. ICLR 2026Mini-cluster Guided Long-tailed Deep Clustering
184. ICLR 2026Mitigating Spurious Correlation via Distributionally Robust Learning with Hierarchical Ambiguity Sets
185. ICLR 2026Modeling the Density of Pixel-level Self-supervised Embeddings for Unsupervised Pathology Segmentation in Medical CT
186. ICLR 2026Multi-View Encoders for Performance Prediction in LLM-Based Agentic Workflows
187. ICLR 2026Multimodal Classification via Total Correlation Maximization
188. ICLR 2026NAB: Neural Adaptive Binning for Sparse-View CT reconstruction
189. ICLR 2026Navigating the Latent Space Dynamics of Neural Models
190. ICLR 2026Neural Sum-of-Squares: Certifying the Nonnegativity of Polynomials with Transformers
191. ICLR 2026Non-Clashing Teaching in Graphs: Algorithms, Complexity, and Bounds
192. ICLR 2026On the Alignment Between Supervised and Self-Supervised Contrastive Learning
193. ICLR 2026On the Lipschitz Continuity of Set Aggregation Functions and Neural Networks for Sets
194. ICLR 2026On the Predictive Power of Representation Dispersion in Language Models
195. ICLR 2026On the Universality and Complexity of GNN for Solving Second-order Cone Programs
196. ICLR 2026On the Wasserstein Geodesic Principal Component Analysis of probability measures
197. ICLR 2026Optimal Brain Restoration for Joint Quantization and Sparsification of LLMs
198. ICLR 2026OrthoRF: Exploring Orthogonality in Object-Centric Representations
199. ICLR 2026PHyCLIP: $\ell_1$-Product of Hyperbolic Factors Unifies Hierarchy and Compositionality in Vision-Language Representation Learning
200. ICLR 2026Poly-attention: a general scheme for higher-order self-attention

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.