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

2,682 papers, page 12 of 54

551. ICML 2026The benefits of full data shuffle, now with optimal I/O cost: $k$-wise independence and matrix transposition to the rescue
552. ICML 2026The Consistency Dilemma in LLMs: Generator-Evaluator Agreement and Vulnerability to Mistakes
553. ICML 2026The Cost of Information: Phase Transitions in Contextual Bandits with Paid Observations
554. ICML 2026The Loss Is Not Enough: Sampling Conditions and Inductive Bias in Contrastive Representation Learning
555. ICML 2026The Relative Instability of Model Comparison with Cross-validation
556. ICML 2026Theoretical Investigation on Inductive Bias of Isolation Forest
557. ICML 2026Thoughtbubbles: an Unsupervised Method for Parallel Thinking in Latent Space
558. ICML 2026TimeLAVA: Learning-Agnostic Valuation for Time Series Data
559. ICML 2026ToaSt: Token Channel Selection and Structured Pruning for Efficient ViT
560. ICML 2026Toward Scalable and Valid Conditional Independence Testing with Spectral Representations
561. ICML 2026Toward Structural Multimodal Representations: Specialization, Selection, and Sparsification via Mixture-of-Experts
562. ICML 2026Towards One-for-All Anomaly Detection for Tabular Data
563. ICML 2026Towards Uniformity and Alignment for Multimodal Representation Learning
564. ICML 2026Tracing the Persona Circuit: How Large Language Models Encode and Express Character Traits
565. ICML 2026Trajectory-Aware Certified Decentralized Unlearning via SGD Stability
566. ICML 2026Transfer Learning in High-dimensional Ising Models
567. ICML 2026Transfer Learning in Nonparametric Regression with Deep ReLU Networks
568. ICML 2026Transformer Circuits Can Realize Clustering Algorithms
569. ICML 2026Transport Clustering: Solving Low-Rank Optimal Transport via Clustering
570. ICML 2026Transporting Task Vectors across Different Architectures without Training
571. ICML 2026Tree-Structured Orthonormal Decomposition of the Aitchison Simplex
572. ICML 2026TsLLM: Augmenting LLMs for General Time Series Understanding and Prediction
573. ICML 2026TuneAhead: Predicting Fine-tuning Performance Before Training Begins
574. ICML 2026Tuning-Free One-Class Discriminant Learning for Tabular Anomaly Detection
575. ICML 2026Two-Layer Linear Auto-Regressive Models Estimate Latent States
576. ICML 2026Two-Stage Unit Tying for Simplifying Differentiable Logic Gate Networks
577. ICML 2026Uncovering Bias Mechanisms in Observational Studies
578. ICML 2026Understand and Accelerate Memory Processing Pipeline for Large Language Model Inference
579. ICML 2026Understanding the Gaps in Satisficing Bandits
580. ICML 2026Understanding Transfer Learning of RNA Foundation Models on Downstream Tasks
581. ICML 2026Unfolded Laplacian Spectral Embedding: A Theoretically Grounded Approach to Dynamic Network Representation
582. ICML 2026UniFast-HGR: Scalable and Efficient Maximal Correlation for Multimodal Models
583. ICML 2026Unifying and Optimizing Data Values for Selection via Sequential Decision-Making
584. ICML 2026Unifying Stacking and Cascading for Efficient Ensemble Inference
585. ICML 2026Universal Algorithm-Implicit Learning
586. ICML 2026Universal Representation of Generalized Convex Functions and their Gradients
587. ICML 2026Unlocking the Potential of Continual Model Merging: An ODE Perspective
588. ICML 2026Unsupervised Camouflaged Object Detection with Dual-Eigenvector Spectral Pseudo-Labeling and Contrastive Refinement
589. ICML 2026Unsupervised Diffusion Solver for Combinatorial Optimization via Combinatorial Adjoint Matching
590. ICML 2026Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability
591. ICML 2026Unsupervised Hierarchical Skill Discovery
592. ICML 2026Unsupervised Neural Langevin Sampler for Mixed Integer Linear Programming
593. ICML 2026Unsupervised Partner Design Enables Robust Ad-hoc Teamwork
594. ICML 2026Unsupervised Process-Aware Coreset Selection for In-Context Learning
595. ICML 2026Untied Ulysses: Memory-Efficient Context Parallelism via Headwise Chunking
596. ICML 2026Unveiling And Addressing Dimensional Collapse In Vector Quantization Models Via Codebook Regularization
597. ICML 2026Unveiling Multi-regime Patterns in SciML: Distinct Failure Modes and Regime-specific Optimization
598. ICML 2026USE: A Unified Self-Ensembling Framework for Test-Time Prompt Tuning
599. ICML 2026Variational Entropic Optimal Transport
600. ICML 2026Von Mises-Fisher Mixture Model with Dynamic Shrinkage for Realistic Test-Time Transduction

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.