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

236 papers, page 2 of 5

51. ICLR 2024Designing Skill-Compatible AI: Methodologies and Frameworks in Chess
52. ICLR 2024Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
53. ICLR 2024Discovering modular solutions that generalize compositionally
54. ICLR 2024Dissecting learning and forgetting in language model finetuning
55. ICLR 2024Diving Segmentation Model into Pixels
56. ICLR 2024Do Generated Data Always Help Contrastive Learning?
57. ICLR 2024DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
58. ICLR 2024Dynamic Sparse Training with Structured Sparsity
59. ICLR 2024DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization
60. ICLR 2024Early Stopping Against Label Noise Without Validation Data
61. ICLR 2024Effective Data Augmentation With Diffusion Models
62. ICLR 2024Efficient ConvBN Blocks for Transfer Learning and Beyond
63. ICLR 2024Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation
64. ICLR 2024Efficient local linearity regularization to overcome catastrophic overfitting
65. ICLR 2024Energy-guided Entropic Neural Optimal Transport
66. ICLR 2024Enhancing Tail Performance in Extreme Classifiers by Label Variance Reduction
67. ICLR 2024Ensemble Distillation for Unsupervised Constituency Parsing
68. ICLR 2024Epitopological learning and Cannistraci-Hebb network shape intelligence brain-inspired theory for ultra-sparse advantage in deep learning
69. ICLR 2024Exploring Diffusion Time-steps for Unsupervised Representation Learning
70. ICLR 2024Exploring the Promise and Limits of Real-Time Recurrent Learning
71. ICLR 2024Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
72. ICLR 2024Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
73. ICLR 2024Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
74. ICLR 2024Faster Approximation of Probabilistic and Distributional Values via Least Squares
75. ICLR 2024Federated Wasserstein Distance
76. ICLR 2024FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent
77. ICLR 2024FedImpro: Measuring and Improving Client Update in Federated Learning
78. ICLR 2024FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
79. ICLR 2024Finite Scalar Quantization: VQ-VAE Made Simple
80. ICLR 2024Flow Matching on General Geometries
81. ICLR 2024From Graphs to Hypergraphs: Hypergraph Projection and its Reconstruction
82. ICLR 2024G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
83. ICLR 2024GAIA: a benchmark for General AI Assistants
84. ICLR 2024General Graph Random Features
85. ICLR 2024General Stability Analysis for Zeroth-Order Optimization Algorithms
86. ICLR 2024Generalized Neural Sorting Networks with Error-Free Differentiable Swap Functions
87. ICLR 2024Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks
88. ICLR 2024Ghost on the Shell: An Expressive Representation of General 3D Shapes
89. ICLR 2024Grokking as a First Order Phase Transition in Two Layer Networks
90. ICLR 2024Grounded Object-Centric Learning
91. ICLR 2024Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram
92. ICLR 2024How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations
93. ICLR 2024How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
94. ICLR 2024Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing
95. ICLR 2024Hyper Evidential Deep Learning to Quantify Composite Classification Uncertainty
96. ICLR 2024Hypergraph Dynamic System
97. ICLR 2024HYPO: Hyperspherical Out-Of-Distribution Generalization
98. ICLR 2024Identifiable Latent Polynomial Causal Models through the Lens of Change
99. ICLR 2024iGraphMix: Input Graph Mixup Method for Node Classification
100. ICLR 2024Image Background Serves as Good Proxy for Out-of-distribution Data

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.