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

203 papers, page 4 of 5

151. NeurIPS 2025Separating the 'what' and 'how' of compositional computation to enable reuse and continual learning
152. NeurIPS 2025Shapley-Based Data Valuation for Weighted $k$-Nearest Neighbors
153. NeurIPS 2025SHGR: A Generalized Maximal Correlation Coefficient
154. NeurIPS 2025SNAP: Low-Latency Test-Time Adaptation with Sparse Updates
155. NeurIPS 2025SORTeD Rashomon Sets of Sparse Decision Trees: Anytime Enumeration
156. NeurIPS 2025Spatiotemporal Consensus with Scene Prior for Unsupervised Domain Adaptive Person Search
157. NeurIPS 2025Spectral Graph Coarsening Using Inner Product Preservation and the Grassmann Manifold
158. NeurIPS 2025SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
159. NeurIPS 2025SPICED: A Synaptic Homeostasis-Inspired Framework for Unsupervised Continual EEG Decoding
160. NeurIPS 2025Split conformal classification with unsupervised calibration
161. NeurIPS 2025Stability and Oracle Inequalities for Optimal Transport Maps between General Distributions
162. NeurIPS 2025Stochastic Forward-Forward Learning through Representational Dimensionality Compression
163. NeurIPS 2025Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization
164. NeurIPS 2025Structured Temporal Causality for Interpretable Multivariate Time Series Anomaly Detection
165. NeurIPS 2025Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes
166. NeurIPS 2025The First Few Tokens Are All You Need: An Efficient and Effective Unsupervised Prefix Fine-Tuning Method for Reasoning Models
167. NeurIPS 2025Theoretical Insights into In-context Learning with Unlabeled Data
168. NeurIPS 2025Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining
169. NeurIPS 2025Tightening Regret Lower and Upper Bounds in Restless Rising Bandits
170. NeurIPS 2025Token Perturbation Guidance for Diffusion Models
171. NeurIPS 2025Towards a General Attention Framework on Gyrovector Spaces for Matrix Manifolds
172. NeurIPS 2025Towards a Pairwise Ranking Model with Orderliness and Monotonicity for Label Enhancement
173. NeurIPS 2025Towards General Modality Translation with Contrastive and Predictive Latent Diffusion Bridge
174. NeurIPS 2025Towards Unsupervised Domain Bridging via Image Degradation in Semantic Segmentation
175. NeurIPS 2025Towards Unsupervised Open-Set Graph Domain Adaptation via Dual Reprogramming
176. NeurIPS 2025Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN
177. NeurIPS 2025TPP-SD: Accelerating Transformer Point Process Sampling with Speculative Decoding
178. NeurIPS 2025Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
179. NeurIPS 2025Transductive Conformal Inference for Full Ranking
180. NeurIPS 2025Tree Ensemble Explainability through the Hoeffding Functional Decomposition and TreeHFD Algorithm
181. NeurIPS 2025Tree-Sliced Entropy Partial Transport
182. NeurIPS 2025TREND: Unsupervised 3D Representation Learning via Temporal Forecasting for LiDAR Perception
183. NeurIPS 2025Two‑Stage Learning of Stabilizing Neural Controllers via Zubov Sampling and Iterative Domain Expansion
184. NeurIPS 2025U-CAN: Unsupervised Point Cloud Denoising with Consistency-Aware Noise2Noise Matching
185. NeurIPS 2025UGM2N: An Unsupervised and Generalizable Mesh Movement Network via M-Uniform Loss
186. NeurIPS 2025UGoDIT: Unsupervised Group Deep Image Prior Via Transferable Weights
187. NeurIPS 2025Ultrametric Cluster Hierarchies: I Want ‘em All!
188. NeurIPS 2025Uncertainty Estimation by Flexible Evidential Deep Learning
189. NeurIPS 2025Uni-RL: Unifying Online and Offline RL via Implicit Value Regularization
190. NeurIPS 2025UniGist: Towards General and Hardware-aligned Sequence-level Long Context Compression
191. NeurIPS 2025Universal Sequence Preconditioning
192. NeurIPS 2025Unlabeled Data Improves Fine-Grained Image Zero-shot Classification with Multimodal LLMs
193. NeurIPS 2025Unsupervised Federated Graph Learning
194. NeurIPS 2025Unsupervised Learning for Optimal Transport plan prediction between unbalanced graphs
195. NeurIPS 2025Unsupervised Trajectory Optimization for 3D Registration in Serial Section Electron Microscopy using Neural ODEs
196. NeurIPS 2025Unveiling Transformer Perception by Exploring Input Manifolds
197. NeurIPS 2025Valid Selection among Conformal Sets
198. NeurIPS 2025VL-SAM-V2: Open-World Object Detection with General and Specific Query Fusion
199. NeurIPS 2025Wasserstein Transfer Learning
200. NeurIPS 2025Weak-shot Keypoint Estimation via Keyness and Correspondence Transfer

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.