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

833 papers, page 16 of 17

751. NeurIPS 2023ReContrast: Domain-Specific Anomaly Detection via Contrastive Reconstruction
752. NeurIPS 2023Recovering from Out-of-sample States via Inverse Dynamics in Offline Reinforcement Learning
753. NeurIPS 2023Reducing Blackwell and Average Optimality to Discounted MDPs via the Blackwell Discount Factor
754. NeurIPS 2023Regularity as Intrinsic Reward for Free Play
755. NeurIPS 2023ReHLine: Regularized Composite ReLU-ReHU Loss Minimization with Linear Computation and Linear Convergence
756. NeurIPS 2023Reinforcement Learning with Fast and Forgetful Memory
757. NeurIPS 2023Reliable learning in challenging environments
758. NeurIPS 2023Representation Learning via Consistent Assignment of Views over Random Partitions
759. NeurIPS 2023Resilient Constrained Learning
760. NeurIPS 2023Responsible AI (RAI) Games and Ensembles
761. NeurIPS 2023Reward Finetuning for Faster and More Accurate Unsupervised Object Discovery
762. NeurIPS 2023Robust and Actively Secure Serverless Collaborative Learning
763. NeurIPS 2023Rotating Features for Object Discovery
764. NeurIPS 2023SALSA VERDE: a machine learning attack on LWE with sparse small secrets
765. NeurIPS 2023Sample based Explanations via Generalized Representers
766. NeurIPS 2023Scenario Diffusion: Controllable Driving Scenario Generation With Diffusion
767. NeurIPS 2023Schema-learning and rebinding as mechanisms of in-context learning and emergence
768. NeurIPS 2023Selective Sampling and Imitation Learning via Online Regression
769. NeurIPS 2023Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
770. NeurIPS 2023Self-supervised Object-Centric Learning for Videos
771. NeurIPS 2023SEVA: Leveraging sketches to evaluate alignment between human and machine visual abstraction
772. NeurIPS 2023SG×P : A Sorghum Genotype × Phenotype Prediction Dataset and Benchmark
773. NeurIPS 2023Shape Non-rigid Kinematics (SNK): A Zero-Shot Method for Non-Rigid Shape Matching via Unsupervised Functional Map Regularized Reconstruction
774. NeurIPS 2023Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
775. NeurIPS 2023SimFBO: Towards Simple, Flexible and Communication-efficient Federated Bilevel Learning
776. NeurIPS 2023SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
777. NeurIPS 2023Simple and Asymmetric Graph Contrastive Learning without Augmentations
778. NeurIPS 2023Simple, Scalable and Effective Clustering via One-Dimensional Projections
779. NeurIPS 2023Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming
780. NeurIPS 2023Slot-guided Volumetric Object Radiance Fields
781. NeurIPS 2023SmooSeg: Smoothness Prior for Unsupervised Semantic Segmentation
782. NeurIPS 2023Smoothed Online Learning for Prediction in Piecewise Affine Systems
783. NeurIPS 2023Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
784. NeurIPS 2023StableFDG: Style and Attention Based Learning for Federated Domain Generalization
785. NeurIPS 2023Statistical Insights into HSIC in High Dimensions
786. NeurIPS 2023Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration
787. NeurIPS 2023Tackling Heavy-Tailed Rewards in Reinforcement Learning with Function Approximation: Minimax Optimal and Instance-Dependent Regret Bounds
788. NeurIPS 2023Tanimoto Random Features for Scalable Molecular Machine Learning
789. NeurIPS 2023Temporal Robustness against Data poisoning
790. NeurIPS 2023Temporally Disentangled Representation Learning under Unknown Nonstationarity
791. NeurIPS 2023Tester-Learners for Halfspaces: Universal Algorithms
792. NeurIPS 2023The Equivalence of Dynamic and Strategic Stability under Regularized Learning in Games
793. NeurIPS 2023The Grand Illusion: The Myth of Software Portability and Implications for ML Progress.
794. NeurIPS 2023The Pick-to-Learn Algorithm: Empowering Compression for Tight Generalization Bounds and Improved Post-training Performance
795. NeurIPS 2023The Pursuit of Human Labeling: A New Perspective on Unsupervised Learning
796. NeurIPS 2023The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
797. NeurIPS 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics
798. NeurIPS 2023Topological Obstructions and How to Avoid Them
799. NeurIPS 2023Towards a Unified Analysis of Kernel-based Methods Under Covariate Shift
800. NeurIPS 2023Towards Free Data Selection with General-Purpose Models

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.