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 10 of 13

451. NeurIPS 2023Fundamental Limits and Tradeoffs in Invariant Representation Learning
452. NeurIPS 2023General Munchausen Reinforcement Learning with Tsallis Kullback-Leibler Divergence
453. NeurIPS 2023Generalized equivalences between subsampling and ridge regularization
454. NeurIPS 2023GLIME: General, Stable and Local LIME Explanation
455. NeurIPS 2023Globally injective and bijective neural operators
456. NeurIPS 2023Granger Components Analysis: Unsupervised learning of latent temporal dependencies
457. NeurIPS 2023Graph Contrastive Learning with Stable and Scalable Spectral Encoding
458. NeurIPS 2023Graph Convolutional Kernel Machine versus Graph Convolutional Networks
459. NeurIPS 2023GUST: Combinatorial Generalization by Unsupervised Grouping with Neuronal Coherence
460. NeurIPS 2023H-nobs: Achieving Certified Fairness and Robustness in Distributed Learning on Heterogeneous Datasets
461. NeurIPS 2023H3T: Efficient Integration of Memory Optimization and Parallelism for Large-scale Transformer Training
462. NeurIPS 2023Harnessing the power of choices in decision tree learning
463. NeurIPS 2023Have it your way: Individualized Privacy Assignment for DP-SGD
464. NeurIPS 2023Hierarchical Vector Quantized Transformer for Multi-class Unsupervised Anomaly Detection
465. NeurIPS 2023How a Student becomes a Teacher: learning and forgetting through Spectral methods
466. NeurIPS 2023How many samples are needed to leverage smoothness?
467. NeurIPS 2023How to Select Which Active Learning Strategy is Best Suited for Your Specific Problem and Budget
468. NeurIPS 2023HubRouter: Learning Global Routing via Hub Generation and Pin-hub Connection
469. NeurIPS 2023Human-Aligned Calibration for AI-Assisted Decision Making
470. NeurIPS 2023ID and OOD Performance Are Sometimes Inversely Correlated on Real-world Datasets
471. NeurIPS 2023Implicit Regularization in Over-Parameterized Support Vector Machine
472. NeurIPS 2023Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
473. NeurIPS 2023Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms
474. NeurIPS 2023Improved Frequency Estimation Algorithms with and without Predictions
475. NeurIPS 2023In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer
476. NeurIPS 2023Incentives in Federated Learning: Equilibria, Dynamics, and Mechanisms for Welfare Maximization
477. NeurIPS 2023Incentives in Private Collaborative Machine Learning
478. NeurIPS 2023Incentivizing Honesty among Competitors in Collaborative Learning and Optimization
479. NeurIPS 2023Information Maximizing Curriculum: A Curriculum-Based Approach for Learning Versatile Skills
480. NeurIPS 2023InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
481. NeurIPS 2023InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
482. NeurIPS 2023Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
483. NeurIPS 2023Invariant Learning via Probability of Sufficient and Necessary Causes
484. NeurIPS 2023Inverse Reinforcement Learning with the Average Reward Criterion
485. NeurIPS 2023Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning
486. NeurIPS 2023Joint Attribute and Model Generalization Learning for Privacy-Preserving Action Recognition
487. NeurIPS 2023Kernelized Cumulants: Beyond Kernel Mean Embeddings
488. NeurIPS 2023KuaiSim: A Comprehensive Simulator for Recommender Systems
489. NeurIPS 2023Learning and Collusion in Multi-unit Auctions
490. NeurIPS 2023Learning and processing the ordinal information of temporal sequences in recurrent neural circuits
491. NeurIPS 2023Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation
492. NeurIPS 2023Learning Exponential Families from Truncated Samples
493. NeurIPS 2023Learning From Biased Soft Labels
494. NeurIPS 2023Learning Linear Causal Representations from Interventions under General Nonlinear Mixing
495. NeurIPS 2023Learning Motion Refinement for Unsupervised Face Animation
496. NeurIPS 2023Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
497. NeurIPS 2023Learning to Configure Separators in Branch-and-Cut
498. NeurIPS 2023Learning to Discover Skills through Guidance
499. NeurIPS 2023Learning Universal Policies via Text-Guided Video Generation
500. NeurIPS 2023Leveraging sparse and shared feature activations for disentangled representation learning

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.