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

318 papers, page 2 of 7

51. NeurIPS 2023Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
52. NeurIPS 2023Causal Fairness for Outcome Control
53. NeurIPS 2023Causes and Effects of Unanticipated Numerical Deviations in Neural Network Inference Frameworks
54. NeurIPS 2023CEIL: Generalized Contextual Imitation Learning
55. NeurIPS 2023Certification of Distributional Individual Fairness
56. NeurIPS 2023Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
57. NeurIPS 2023Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark
58. NeurIPS 2023ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
59. NeurIPS 2023ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
60. NeurIPS 2023ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
61. NeurIPS 2023Clustering the Sketch: Dynamic Compression for Embedding Tables
62. NeurIPS 2023CODA: Generalizing to Open and Unseen Domains with Compaction and Disambiguation
63. NeurIPS 2023CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra
64. NeurIPS 2023Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
65. NeurIPS 2023Complementary Benefits of Contrastive Learning and Self-Training Under Distribution Shift
66. NeurIPS 2023Complex-valued Neurons Can Learn More but Slower than Real-valued Neurons via Gradient Descent
67. NeurIPS 2023Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy
68. NeurIPS 2023Consensus and Subjectivity of Skin Tone Annotation for ML Fairness
69. NeurIPS 2023Contrast, Attend and Diffuse to Decode High-Resolution Images from Brain Activities
70. NeurIPS 2023Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time
71. NeurIPS 2023Convex and Non-convex Optimization Under Generalized Smoothness
72. NeurIPS 2023Convolutional Neural Operators for robust and accurate learning of PDEs
73. NeurIPS 2023Corruption-Robust Offline Reinforcement Learning with General Function Approximation
74. NeurIPS 2023Creating a Public Repository for Joining Private Data
75. NeurIPS 2023CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation
76. NeurIPS 2023CSLP-AE: A Contrastive Split-Latent Permutation Autoencoder Framework for Zero-Shot Electroencephalography Signal Conversion
77. NeurIPS 2023D$^2$CSG: Unsupervised Learning of Compact CSG Trees with Dual Complements and Dropouts
78. NeurIPS 2023Data-Informed Geometric Space Selection
79. NeurIPS 2023Debiased and Denoised Entity Recognition from Distant Supervision
80. NeurIPS 2023Decision-Aware Actor-Critic with Function Approximation and Theoretical Guarantees
81. NeurIPS 2023Decompose Novel into Known: Part Concept Learning For 3D Novel Class Discovery
82. NeurIPS 2023Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses
83. NeurIPS 2023Delegated Classification
84. NeurIPS 2023Direction-oriented Multi-objective Learning: Simple and Provable Stochastic Algorithms
85. NeurIPS 2023Disambiguated Attention Embedding for Multi-Instance Partial-Label Learning
86. NeurIPS 2023DISCO-10M: A Large-Scale Music Dataset
87. NeurIPS 2023Discovering General Reinforcement Learning Algorithms with Adversarial Environment Design
88. NeurIPS 2023Disentanglement via Latent Quantization
89. NeurIPS 2023Disentangling Voice and Content with Self-Supervision for Speaker Recognition
90. NeurIPS 2023Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning
91. NeurIPS 2023Distribution Learnability and Robustness
92. NeurIPS 2023Distributionally Robust Skeleton Learning of Discrete Bayesian Networks
93. NeurIPS 2023Double Pessimism is Provably Efficient for Distributionally Robust Offline Reinforcement Learning: Generic Algorithm and Robust Partial Coverage
94. NeurIPS 2023Dynamic Non-monotone Submodular Maximization
95. NeurIPS 2023Dynamic Pricing and Learning with Bayesian Persuasion
96. NeurIPS 2023Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes
97. NeurIPS 2023Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
98. NeurIPS 2023Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
99. NeurIPS 2023Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
100. NeurIPS 2023Equal Opportunity of Coverage in Fair Regression

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.