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 6 of 7

251. NeurIPS 2023Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
252. NeurIPS 2023Schema-learning and rebinding as mechanisms of in-context learning and emergence
253. NeurIPS 2023Selective Sampling and Imitation Learning via Online Regression
254. NeurIPS 2023Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
255. NeurIPS 2023Self-supervised Object-Centric Learning for Videos
256. NeurIPS 2023SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction
257. NeurIPS 2023SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark
258. NeurIPS 2023Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction
259. NeurIPS 2023Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
260. NeurIPS 2023SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
261. NeurIPS 2023SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
262. NeurIPS 2023Simple and Asymmetric Graph Contrastive Learning without Augmentations
263. NeurIPS 2023Simple, Scalable and Effective Clustering via One-Dimensional Projections
264. NeurIPS 2023Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
265. NeurIPS 2023Slot-guided Volumetric Object Radiance Fields
266. NeurIPS 2023SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation
267. NeurIPS 2023Smoothed Online Learning for Prediction in Piecewise Affine Systems
268. NeurIPS 2023Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
269. NeurIPS 2023StableFDG: Style and Attention Based Learning for Federated Domain Generalization
270. NeurIPS 2023Statistical Insights into HSIC in High Dimensions
271. NeurIPS 2023Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration
272. NeurIPS 2023Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
273. NeurIPS 2023Tanimoto Random Features for Scalable Molecular Machine Learning
274. NeurIPS 2023Temporal Robustness against Data poisoning
275. NeurIPS 2023Temporally Disentangled Representation Learning under Unknown Nonstationarity
276. NeurIPS 2023Tester-Learners for Halfspaces: Universal Algorithms
277. NeurIPS 2023The Equivalence of Dynamic and Strategic Stability under Regularized Learning in Games
278. NeurIPS 2023The Grand Illusion: The Myth of Software Portability and Implications for ML Progress.
279. NeurIPS 2023The Pick-to-Learn Algorithm: Empowering Compression for Tight Generalization Bounds and Improved Post-training Performance
280. NeurIPS 2023The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
281. NeurIPS 2023The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
282. NeurIPS 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
283. NeurIPS 2023Topological Obstructions and How to Avoid Them
284. NeurIPS 2023Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift
285. NeurIPS 2023Towards Free Data Selection with General-Purpose Models
286. NeurIPS 2023Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
287. NeurIPS 2023Towards robust and generalizable representations of extracellular data using contrastive learning
288. NeurIPS 2023Trade-off Between Efficiency and Consistency for Removal-based Explanations
289. NeurIPS 2023Transfer learning for atomistic simulations using GNNs and kernel mean embeddings
290. NeurIPS 2023Transfer Learning with Affine Model Transformation
291. NeurIPS 2023Trial matching: capturing variability with data-constrained spiking neural networks
292. NeurIPS 2023UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition
293. NeurIPS 2023Unbalanced Low-rank Optimal Transport Solvers
294. NeurIPS 2023Uncoupled and Convergent Learning in Two-Player Zero-Sum Markov Games with Bandit Feedback
295. NeurIPS 2023Understanding and Improving Feature Learning for Out-of-Distribution Generalization
296. NeurIPS 2023Understanding Few-Shot Learning: Measuring Task Relatedness and Adaptation Difficulty via Attributes
297. NeurIPS 2023Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems
298. NeurIPS 2023Universality and Limitations of Prompt Tuning
299. NeurIPS 2023Unlocking Deterministic Robustness Certification on ImageNet
300. NeurIPS 2023UNSSOR: Unsupervised Neural Speech Separation by Leveraging Over-determined Training Mixtures

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.