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

859 papers, page 15 of 18

701. ICML 2024WISER: Weak Supervision and Supervised Representation Learning to Improve Drug Response Prediction in Cancer
702. ICML 2024Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion
703. ICML 2023A General Representation Learning Framework with Generalization Performance Guarantees
704. ICML 2023A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
705. ICML 2023A Mathematical Model for Curriculum Learning for Parities
706. ICML 2023A Model-Based Method for Minimizing CVaR and Beyond
707. ICML 2023A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks
708. ICML 2023Adaptive Annealed Importance Sampling with Constant Rate Progress
709. ICML 2023Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions
710. ICML 2023Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
711. ICML 2023Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
712. ICML 2023Anchor Sampling for Federated Learning with Partial Client Participation
713. ICML 2023Are Equivariant Equilibrium Approximators Beneficial?
714. ICML 2023Are Neurons Actually Collapsed? On the Fine-Grained Structure in Neural Representations
715. ICML 2023Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
716. ICML 2023Auto-Differentiation of Relational Computations for Very Large Scale Machine Learning
717. ICML 2023AutoCoreset: An Automatic Practical Coreset Construction Framework
718. ICML 2023Behavior Contrastive Learning for Unsupervised Skill Discovery
719. ICML 2023Beyond the Edge of Stability via Two-step Gradient Updates
720. ICML 2023BiBench: Benchmarking and Analyzing Network Binarization
721. ICML 2023Calibrating Multimodal Learning
722. ICML 2023Can Neural Network Memorization Be Localized?
723. ICML 2023Cell-Free Latent Go-Explore
724. ICML 2023Certifying Ensembles: A General Certification Theory with S-Lipschitzness
725. ICML 2023CLUTR: Curriculum Learning via Unsupervised Task Representation Learning
726. ICML 2023Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning Using Independent Component Analysis
727. ICML 2023CoCo: A Coupled Contrastive Framework for Unsupervised Domain Adaptive Graph Classification
728. ICML 2023Combinatorial Neural Bandits
729. ICML 2023ConCerNet: A Contrastive Learning Based Framework for Automated Conservation Law Discovery and Trustworthy Dynamical System Prediction
730. ICML 2023Conditions and Assumptions for Constraint-based Causal Structure Learning
731. ICML 2023Confidence and Dispersity Speak: Characterizing Prediction Matrix for Unsupervised Accuracy Estimation
732. ICML 2023Continual Learners are Incremental Model Generalizers
733. ICML 2023Contrastive Learning Meets Homophily: Two Birds with One Stone
734. ICML 2023Controllability-Aware Unsupervised Skill Discovery
735. ICML 2023Corruption-Robust Algorithms with Uncertainty Weighting for Nonlinear Contextual Bandits and Markov Decision Processes
736. ICML 2023Decentralized SGD and Average-direction SAM are Asymptotically Equivalent
737. ICML 2023Demonstration-free Autonomous Reinforcement Learning via Implicit and Bidirectional Curriculum
738. ICML 2023Deterministic equivalent and error universality of deep random features learning
739. ICML 2023Differentiable and Transportable Structure Learning
740. ICML 2023Dimensionality Reduction for General KDE Mode Finding
741. ICML 2023Discovering Object-Centric Generalized Value Functions From Pixels
742. ICML 2023Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the Machiavelli Benchmark
743. ICML 2023DUET: 2D Structured and Approximately Equivariant Representations
744. ICML 2023Dynamic Regularized Sharpness Aware Minimization in Federated Learning: Approaching Global Consistency and Smooth Landscape
745. ICML 2023E$(n)$ Equivariant Message Passing Simplicial Networks
746. ICML 2023Effective Structured Prompting by Meta-Learning and Representative Verbalizer
747. ICML 2023Entropy-driven Unsupervised Keypoint Representation Learning in Videos
748. ICML 2023Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms
749. ICML 2023Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection
750. ICML 2023Evaluating Unsupervised Denoising Requires Unsupervised Metrics

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.