General ML · unsupervised and semisupervised learning papers, 2023–2026
General machine learning: unsupervised_and_semisupervised_learning
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 2,683 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 318 | 87 | 157 | 87 | 649 |
| 2024 | 118 | 236 | 115 | 84 | 553 |
| 2025 | 203 | 174 | 239 | 66 | 682 |
| 2026 | 194 | 187 | 348 | 70 | 799 |
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
348 papers, page 1 of 7
- ICML 2026$\mu$pscaling small models: Principled warm starts and hyperparameter transfer
- ICML 2026$\texttt{MetaDistill}$: Unlocking the Performance Ceiling for Pretrained Optimizers
- ICML 2026A Benchmark and Framework for Evaluating Next Action Predictions in Spreadsheets
- ICML 2026A Control-Theoretic View of Mamba on Stability and Robustness
- ICML 2026A General Framework for Dynamic Consistent Submodular Maximization
- ICML 2026A General Framework for Fair and Robust Regression
- ICML 2026A General Neural Backbone for Mixed-Integer Linear Optimization via Dual Attention
- ICML 2026A Minimax Approach for Optimal Intervention Policy Learning with Two-Stage Outcomes
- ICML 2026A Probabilistic Framework for LLM-Based Model Discovery
- ICML 2026A Sketch-and-Project Analysis of Subsampled Natural Gradient Algorithms
- ICML 2026A Strictly Proper Scoring Rule and a Calibration Metric for Interval-Censored Data Analysis
- ICML 2026A Studentized Spherical Harmonics–Based Nonparametric Two-Sample Test for Compositional and Directional Data
- ICML 2026A Unified Density Operator View of Flow Control and Merging
- ICML 2026A Unified Framework for Deep Hypergraph Clustering Beyond Homophily
- ICML 2026Accuracy and Normalized Accuracy under Length Bias: Analysis, Guidelines, and a Bayesian Alternative
- ICML 2026Activation Oracles: Training and Evaluating LLMs as General-Purpose Activation Explainers
- ICML 2026Adaptive Estimation and Inference in Semi-parametric Heterogeneous Clustered Multitask Learning via Neyman Orthogonality
- ICML 2026Adaptively Grouped Contextual Bandits for Heterogeneous Human-AI Decision Making with Conformal Prediction Sets
- ICML 2026Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
- ICML 2026AgentSuite: Toward More Reliable Agent Evaluation with a Component-Based Benchmark Auditing Pipeline
- ICML 2026Aggregate Models, Not Explanations: Improving Feature Importance Estimation
- ICML 2026AI Cartography: Mapping the Latent Landscape of AI Benchmark Ecosystems
- ICML 2026Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
- ICML 2026An Asymmetric Latent Factorization-of-Tensors Model for Relation Analysis
- ICML 2026Approximation Error Upper and Lower Bounds for Hölder Class with Transformers
- ICML 2026Approximation Preserving Coresets
- ICML 2026Are Object-Centric Representations Better at Compositional Generalization?
- ICML 2026Are Two Datasets Close Enough With Statistical Significance? A Kernel Distributional Closeness Testing Approach
- ICML 2026Assistive Prompt Mediation: Evaluating Language Models Under Accessibility Constraints
- ICML 2026Attributed Network Alignment: Statistical Limits and Efficient Algorithm
- ICML 2026Automatic Unsupervised Ensemble Outlier Model Selection
- ICML 2026Batch Normalization for Neural Networks on Complex Domains
- ICML 2026Bayes-inspired Integration of Pretrained Priors and Few-Shot Evidence for Few-Shot Classification
- ICML 2026Bayesian model selection and misspecification testing in imaging inverse problems only from noisy and partial measurements
- ICML 2026Being More Lightweight and Practical: Mini-sized Contrastive Learning Pre-trained Models for Fine-grained Traffic Task
- ICML 2026Beyond Buffer Limits: Energy-Based Data Reassembly for Continual Learning
- ICML 2026Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-Supervised Learning
- ICML 2026Beyond Global Alignment: Fine-Grained Motion-Language Retrieval via Pyramidal Shapley-Taylor Learning
- ICML 2026Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering
- ICML 2026Beyond Point Predictions: Manifold Expansion and Dual Alignment for Robust Time Series Distillation
- ICML 2026Beyond Rational Illusion: Behaviorally Realistic Strategic Classification
- ICML 2026BFTS: Thompson Sampling with Bayesian Additive Regression Trees
- ICML 2026Box Thirding: Anytime Best Arm Identification under Insufficient Sampling
- ICML 2026BPL: Generalizable Deepfake Detection via Bias-only Pair-aware Learning
- ICML 2026Branching Diffusion for Point Processes in Time and Space
- ICML 2026Bridging Functional and Representational Similarity via Usable Information
- ICML 2026BTSP-CAM: A Brain-Inspired Geometric Memory for Class-Incremental Learning
- ICML 2026Budgeted Active Experimentation for Treatment Effect Estimation from Observational and Randomized Data
- ICML 2026Capacitated Fair-Range Clustering: Hardness and Approximation Algorithms
- ICML 2026Causal Dependency-Aware Unsupervised Routing for Large Reasoning Models
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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.