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 6 of 16

251. ICLR 2026Unsupervised Learning of Efficient Exploration: Pre-training Adaptive Policies via Self-Imposed Goals
252. ICLR 2026Unsupervised Representation Learning - an Invariant Risk Minimization Perspective
253. ICLR 2026Unsupervised Representation Learning for 3D Mesh Parameterization with Semantic and Visibility Objectives
254. ICLR 2026Watch the Weights: Unsupervised monitoring and control of fine-tuned LLMs
255. ICLR 2026Why Prototypes Collapse: Diagnosing and Preventing Partial Collapse in Prototypical Self-Supervised Learning
256. ICLR 2026ZeroTuning: Unlocking the Initial Token's Power to Enhance Large Language Models Without Training
257. ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
258. ICML 2026$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
259. ICML 2026A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheets
260. ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
261. ICML 2026A General Framework for Dynamic Consistent Submodular Maximization
262. ICML 2026A General Framework for Fair and Robust Regression
263. ICML 2026A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention
264. ICML 2026A Minimax Approach for Optimal Intervention Policy Learning with Two-Stage Outcomes
265. ICML 2026A Probabilistic Framework for LLM-Based Model Discovery
266. ICML 2026A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
267. ICML 2026A Strictly Proper Scoring Rule and a Calibration Metric for Interval-Censored Data Analysis
268. ICML 2026A Studentized Spherical Harmonics–Based Nonparametric Two-Sample Test for Compositional and Directional Data
269. ICML 2026A Unified Density Operator View of Flow Control and Merging
270. ICML 2026A Unified Framework for Deep Hypergraph Clustering Beyond Homophily
271. ICML 2026Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative
272. ICML 2026Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers
273. ICML 2026Adaptive Estimation and Inference in Semi-parametric Heterogeneous Clustered Multitask Learning via Neyman Orthogonality
274. ICML 2026Adaptively Grouped Contextual Bandits for Heterogeneous Human-AI Decision Making with Conformal Prediction Sets
275. ICML 2026Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
276. ICML 2026AgentSuite: Toward More Reliable Agent Evaluation with a Component-Based Benchmark Auditing Pipeline
277. ICML 2026Aggregate Models, Not Explanations: Improving Feature Importance Estimation
278. ICML 2026AI Cartography: Mapping the Latent Landscape of AI Benchmark Ecosystems
279. ICML 2026Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
280. ICML 2026An Asymmetric Latent Factorization-of-Tensors Model for Relation Analysis
281. ICML 2026Approximation Error Upper and Lower Bounds for Hölder Class with Transformers
282. ICML 2026Approximation Preserving Coresets
283. ICML 2026Are Object-Centric Representations Better at Compositional Generalization?
284. ICML 2026Are Two Datasets Close Enough With Statistical Significance? A Kernel Distributional Closeness Testing Approach
285. ICML 2026Assistive Prompt Mediation: Evaluating Language Models Under Accessibility Constraints
286. ICML 2026Attributed Network Alignment: Statistical Limits and Efficient Algorithm
287. ICML 2026Automatic Unsupervised Ensemble Outlier Model Selection
288. ICML 2026Batch Normalization for Neural Networks on Complex Domains
289. ICML 2026Bayes-inspired Integration of Pretrained Priors and Few-Shot Evidence for Few-Shot Classification
290. ICML 2026Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements
291. ICML 2026Being More Lightweight and Practical: Mini-sized Contrastive Learning Pre-trained Models for Fine-grained Traffic Task
292. ICML 2026Beyond Buffer Limits: Energy-Based Data Reassembly for Continual Learning
293. ICML 2026Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-Supervised Learning
294. ICML 2026Beyond Global Alignment: Fine-Grained Motion-Language Retrieval via Pyramidal Shapley-Taylor Learning
295. ICML 2026Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering
296. ICML 2026Beyond Point Predictions: Manifold Expansion and Dual Alignment for Robust Time Series Distillation
297. ICML 2026Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
298. ICML 2026BFTS: Thompson Sampling with Bayesian Additive Regression Trees
299. ICML 2026Box Thirding: Anytime Best Arm Identification under Insufficient Sampling
300. ICML 2026BPL: Generalizable Deepfake Detection via Bias-only Pair-aware Learning

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.