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 11 of 13

501. NeurIPS 2023List and Certificate Complexities in Replicable Learning
502. NeurIPS 2023Lo-Hi: Practical ML Drug Discovery Benchmark
503. NeurIPS 2023Locally Invariant Explanations: Towards Stable and Unidirectional Explanations through Local Invariant Learning
504. NeurIPS 2023Lovász Principle for Unsupervised Graph Representation Learning
505. NeurIPS 2023M$^2$Hub: Unlocking the Potential of Machine Learning for Materials Discovery
506. NeurIPS 2023Machine learning detects terminal singularities
507. NeurIPS 2023Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation
508. NeurIPS 2023Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration
509. NeurIPS 2023Maximum Average Randomly Sampled: A Scale Free and Non-parametric Algorithm for Stochastic Bandits
510. NeurIPS 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
511. NeurIPS 2023Metis: Understanding and Enhancing In-Network Regular Expressions
512. NeurIPS 2023Minimum Description Length and Generalization Guarantees for Representation Learning
513. NeurIPS 2023Mixed Samples as Probes for Unsupervised Model Selection in Domain Adaptation
514. NeurIPS 2023MLFMF: Data Sets for Machine Learning for Mathematical Formalization
515. NeurIPS 2023MMD-Fuse: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting
516. NeurIPS 2023MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under nonparametrized geometrical variability
517. NeurIPS 2023Mobilizing Personalized Federated Learning in Infrastructure-Less and Heterogeneous Environments via Random Walk Stochastic ADMM
518. NeurIPS 2023Model Shapley: Equitable Model Valuation with Black-box Access
519. NeurIPS 2023Model Sparsity Can Simplify Machine Unlearning
520. NeurIPS 2023Multi-body SE(3) Equivariance for Unsupervised Rigid Segmentation and Motion Estimation
521. NeurIPS 2023Multi-Object Representation Learning via Feature Connectivity and Object-Centric Regularization
522. NeurIPS 2023Multi-Prompt Alignment for Multi-Source Unsupervised Domain Adaptation
523. NeurIPS 2023Mutual Information Regularized Offline Reinforcement Learning
524. NeurIPS 2023Near-Optimal Bounds for Learning Gaussian Halfspaces with Random Classification Noise
525. NeurIPS 2023Necessary and Sufficient Conditions for Optimal Decision Trees using Dynamic Programming
526. NeurIPS 2023Neural Harmonics: Bridging Spectral Embedding and Matrix Completion in Self-Supervised Learning
527. NeurIPS 2023Neural Modulation for Flash Memory: An Unsupervised Learning Framework for Improved Reliability
528. NeurIPS 2023NeuralGF: Unsupervised Point Normal Estimation by Learning Neural Gradient Function
529. NeurIPS 2023No-Regret Learning in Dynamic Competition with Reference Effects Under Logit Demand
530. NeurIPS 2023Nonparametric Teaching for Multiple Learners
531. NeurIPS 2023OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents
532. NeurIPS 2023Object-centric Learning with Cyclic Walks between Parts and Whole
533. NeurIPS 2023Object-Centric Slot Diffusion
534. NeurIPS 2023On Proper Learnability between Average- and Worst-case Robustness
535. NeurIPS 2023On Robust Streaming for Learning with Experts: Algorithms and Lower Bounds
536. NeurIPS 2023On skip connections and normalisation layers in deep optimisation
537. NeurIPS 2023On the Convergence of No-Regret Learning Dynamics in Time-Varying Games
538. NeurIPS 2023On the Importance of Feature Separability in Predicting Out-Of-Distribution Error
539. NeurIPS 2023On the Interplay between Social Welfare and Tractability of Equilibria
540. NeurIPS 2023On the Robustness of Removal-Based Feature Attributions
541. NeurIPS 2023On the Role of Entanglement and Statistics in Learning
542. NeurIPS 2023One Fits All: Power General Time Series Analysis by Pretrained LM
543. NeurIPS 2023Online Label Shift: Optimal Dynamic Regret meets Practical Algorithms
544. NeurIPS 2023Operator Learning with Neural Fields: Tackling PDEs on General Geometries
545. NeurIPS 2023Optimal and Fair Encouragement Policy Evaluation and Learning
546. NeurIPS 2023Optimal Guarantees for Algorithmic Reproducibility and Gradient Complexity in Convex Optimization
547. NeurIPS 2023Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection
548. NeurIPS 2023Optimal privacy guarantees for a relaxed threat model: Addressing sub-optimal adversaries in differentially private machine learning
549. NeurIPS 2023Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond $1+\alpha$ Moments
550. NeurIPS 2023Overcoming Recency Bias of Normalization Statistics in Continual Learning: Balance and Adaptation

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.