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 12 of 13

551. NeurIPS 2023Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies
552. NeurIPS 2023Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsing
553. NeurIPS 2023Partial Counterfactual Identification of Continuous Outcomes with a Curvature Sensitivity Model
554. NeurIPS 2023Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage
555. NeurIPS 2023Partial Multi-Label Learning with Probabilistic Graphical Disambiguation
556. NeurIPS 2023PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
557. NeurIPS 2023Physics-Driven ML-Based Modelling for Correcting Inverse Estimation
558. NeurIPS 2023PLASTIC: Improving Input and Label Plasticity for Sample Efficient Reinforcement Learning
559. NeurIPS 2023Posterior Sampling for Competitive RL: Function Approximation and Partial Observation
560. NeurIPS 2023Practical Differentially Private Hyperparameter Tuning with Subsampling
561. NeurIPS 2023Prediction and Control in Continual Reinforcement Learning
562. NeurIPS 2023Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression
563. NeurIPS 2023Promises and Pitfalls of Threshold-based Auto-labeling
564. NeurIPS 2023Proportional Response: Contextual Bandits for Simple and Cumulative Regret Minimization
565. NeurIPS 2023Provably Efficient Offline Goal-Conditioned Reinforcement Learning with General Function Approximation and Single-Policy Concentrability
566. NeurIPS 2023QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learning
567. NeurIPS 2023ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction
568. NeurIPS 2023Recovering from Out-of-sample States via Inverse Dynamics in Offline Reinforcement Learning
569. NeurIPS 2023Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor
570. NeurIPS 2023Regularity as Intrinsic Reward for Free Play
571. NeurIPS 2023ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
572. NeurIPS 2023Reinforcement Learning with Fast and Forgetful Memory
573. NeurIPS 2023Reliable learning in challenging environments
574. NeurIPS 2023Representation Learning via Consistent Assignment of Views over Random Partitions
575. NeurIPS 2023Resilient Constrained Learning
576. NeurIPS 2023Responsible AI (RAI) Games and Ensembles
577. NeurIPS 2023Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
578. NeurIPS 2023Robust and Actively Secure Serverless Collaborative Learning
579. NeurIPS 2023Rotating Features for Object Discovery
580. NeurIPS 2023SALSA VERDE: a machine learning attack on LWE with sparse small secrets
581. NeurIPS 2023Sample based Explanations via Generalized Representers
582. NeurIPS 2023Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
583. NeurIPS 2023Schema-learning and rebinding as mechanisms of in-context learning and emergence
584. NeurIPS 2023Selective Sampling and Imitation Learning via Online Regression
585. NeurIPS 2023Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
586. NeurIPS 2023Self-supervised Object-Centric Learning for Videos
587. NeurIPS 2023SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction
588. NeurIPS 2023SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark
589. NeurIPS 2023Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction
590. NeurIPS 2023Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
591. NeurIPS 2023SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
592. NeurIPS 2023SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
593. NeurIPS 2023Simple and Asymmetric Graph Contrastive Learning without Augmentations
594. NeurIPS 2023Simple, Scalable and Effective Clustering via One-Dimensional Projections
595. NeurIPS 2023Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
596. NeurIPS 2023Slot-guided Volumetric Object Radiance Fields
597. NeurIPS 2023SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation
598. NeurIPS 2023Smoothed Online Learning for Prediction in Piecewise Affine Systems
599. NeurIPS 2023Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
600. NeurIPS 2023StableFDG: Style and Attention Based Learning for Federated Domain Generalization

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.