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

682 papers, page 12 of 14

551. NeurIPS 2025Fast Training of Large Kernel Models with Delayed Projections
552. NeurIPS 2025FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
553. NeurIPS 2025Flatness is Necessary, Neural Collapse is Not: Rethinking Generalization via Grokking
554. NeurIPS 2025Flux4D: Flow-based Unsupervised 4D Reconstruction
555. NeurIPS 2025Fréchet Geodesic Boosting
556. NeurIPS 2025Generalization Guarantees for Learning Score-Based Branch-and-Cut Policies in Integer Programming
557. NeurIPS 2025Generalizing while preserving monotonicity in comparison-based preference learning models
558. NeurIPS 2025GPLQ: A General, Practical, and Lightning QAT Method for Vision Transformers
559. NeurIPS 2025Graph Few-Shot Learning via Adaptive Spectrum Experts and Cross-Set Distribution Calibration
560. NeurIPS 2025Graph–Smoothed Bayesian Black-Box Shift Estimator and Its Information Geometry
561. NeurIPS 2025Hierarchical Retrieval: The Geometry and a Pretrain-Finetune Recipe
562. NeurIPS 2025How many measurements are enough? Bayesian recovery in inverse problems with general distributions
563. NeurIPS 2025Hybrid-Collaborative Augmentation and Contrastive Sample Adaptive-Differential Awareness for Robust Attributed Graph Clustering
564. NeurIPS 2025IA-GGAD: Zero-shot Generalist Graph Anomaly Detection via Invariant and Affinity Learning
565. NeurIPS 2025Imbalances in Neurosymbolic Learning: Characterization and Mitigating Strategies
566. NeurIPS 2025Implicit Bias of Spectral Descent and Muon on Multiclass Separable Data
567. NeurIPS 2025Improved Algorithms for Overlapping and Robust Clustering of Edge-Colored Hypergraphs: An LP-Based Combinatorial Approach
568. NeurIPS 2025Improved Confidence Regions and Optimal Algorithms for Online and Offline Linear MNL Bandits
569. NeurIPS 2025Improving Regret Approximation for Unsupervised Dynamic Environment Generation
570. NeurIPS 2025Improving Task-Specific Multimodal Sentiment Analysis with General MLLMs via Prompting
571. NeurIPS 2025Incentivizing Desirable Effort Profiles in Strategic Classification: The Role of Causality and Uncertainty
572. NeurIPS 2025Incomplete Multi-view Clustering via Hierarchical Semantic Alignment and Cooperative Completion
573. NeurIPS 2025Incomplete Multi-view Deep Clustering with Data Imputation and Alignment
574. NeurIPS 2025Interactive and Hybrid Imitation Learning: Provably Beating Behavior Cloning
575. NeurIPS 2025Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
576. NeurIPS 2025KAIROS: Scalable Model-Agnostic Data Valuation
577. NeurIPS 2025KSP: Kolmogorov-Smirnov metric-based Post-Hoc Calibration for Survival Analysis
578. NeurIPS 2025Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification
579. NeurIPS 2025Learning single index models via harmonic decomposition
580. NeurIPS 2025Learning to Learn with Contrastive Meta-Objective
581. NeurIPS 2025Learning with Restricted Boltzmann Machines: Asymptotics of AMP and GD in High Dimensions
582. NeurIPS 2025Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projections
583. NeurIPS 2025LLM Meeting Decision Trees on Tabular Data
584. NeurIPS 2025Localized Data Shapley: Accelerating Valuation for Nearest Neighbor Algorithms
585. NeurIPS 2025Long-tailed Recognition with Model Rebalancing
586. NeurIPS 2025Looking Into the Water by Unsupervised Learning of the Surface Shape
587. NeurIPS 2025LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders
588. NeurIPS 2025Luminance-Aware Statistical Quantization: Unsupervised Hierarchical Learning for Illumination Enhancement
589. NeurIPS 2025MAP Estimation with Denoisers: Convergence Rates and Guarantees
590. NeurIPS 2025Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting
591. NeurIPS 2025MetaSlot: Break Through the Fixed Number of Slots in Object-Centric Learning
592. NeurIPS 2025Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
593. NeurIPS 2025Model Inversion with Layer-Specific Modeling and Alignment for Data-Free Continual Learning
594. NeurIPS 2025Mol-LLaMA: Towards General Understanding of Molecules in Large Molecular Language Model
595. NeurIPS 2025Multiresolution Analysis and Statistical Thresholding on Dynamic Networks
596. NeurIPS 2025Nearly-Linear Time and Massively Parallel Algorithms for $k$-anonymity
597. NeurIPS 2025Neural Fractional Attention Differential Equations
598. NeurIPS 2025Neural Mutual Information Estimation with Vector Copulas
599. NeurIPS 2025Neural Networks for Learnable and Scalable Influence Estimation of Instruction Fine-Tuning Data
600. NeurIPS 2025Non-exchangeable Conformal Prediction with Optimal Transport: Tackling Distribution Shift with Unlabeled Data

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.