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

649 papers, page 9 of 13

401. NeurIPS 2023Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time
402. NeurIPS 2023Convex and Non-convex Optimization Under Generalized Smoothness
403. NeurIPS 2023Convolutional Neural Operators for robust and accurate learning of PDEs
404. NeurIPS 2023Corruption-Robust Offline Reinforcement Learning with General Function Approximation
405. NeurIPS 2023Creating a Public Repository for Joining Private Data
406. NeurIPS 2023CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation
407. NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
408. NeurIPS 2023D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts
409. NeurIPS 2023Data-Informed Geometric Space Selection
410. NeurIPS 2023Debiased and Denoised Entity Recognition from Distant Supervision
411. NeurIPS 2023Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
412. NeurIPS 2023Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery
413. NeurIPS 2023Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses
414. NeurIPS 2023Delegated Classification
415. NeurIPS 2023Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
416. NeurIPS 2023Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
417. NeurIPS 2023DISCO-10M: A Large-Scale Music Dataset
418. NeurIPS 2023Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
419. NeurIPS 2023Disentanglement via Latent Quantization
420. NeurIPS 2023Disentangling Voice and Content with Self-Supervision for Speaker Recognition
421. NeurIPS 2023Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning
422. NeurIPS 2023Distribution Learnability and Robustness
423. NeurIPS 2023Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
424. NeurIPS 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
425. NeurIPS 2023Dynamic Non-monotone Submodular Maximization
426. NeurIPS 2023Dynamic Pricing and Learning with Bayesian Persuasion
427. NeurIPS 2023Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes
428. NeurIPS 2023Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
429. NeurIPS 2023Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
430. NeurIPS 2023Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
431. NeurIPS 2023Equal Opportunity of Coverage in Fair Regression
432. NeurIPS 2023Equivariant Single View Pose Prediction Via Induced and Restriction Representations
433. NeurIPS 2023Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors
434. NeurIPS 2023Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
435. NeurIPS 2023Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
436. NeurIPS 2023Explain Any Concept: Segment Anything Meets Concept-Based Explanation
437. NeurIPS 2023Explaining Predictive Uncertainty with Information Theoretic Shapley Values
438. NeurIPS 2023f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences
439. NeurIPS 2023FABind: Fast and Accurate Protein-Ligand Binding
440. NeurIPS 2023Face Reconstruction from Facial Templates by Learning Latent Space of a Generator Network
441. NeurIPS 2023Fair Allocation of Indivisible Chores: Beyond Additive Costs
442. NeurIPS 2023Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
443. NeurIPS 2023Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
444. NeurIPS 2023Fast and Regret Optimal Best Arm Identification: Fundamental Limits and Low-Complexity Algorithms
445. NeurIPS 2023Fed-CO$_{2}$: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning
446. NeurIPS 2023Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds
447. NeurIPS 2023Federated Learning with Manifold Regularization and Normalized Update Reaggregation
448. NeurIPS 2023Federated Spectral Clustering via Secure Similarity Reconstruction
449. NeurIPS 2023FiGURe: Simple and Efficient Unsupervised Node Representations with Filter Augmentations
450. NeurIPS 2023First- and Second-Order Bounds for Adversarial Linear Contextual Bandits

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.