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

194 papers, page 2 of 4

51. NeurIPS 2026Fixed-Size Active Statistical Inference
52. NeurIPS 2026FLAME: Flow Enhanced Legendre Memory Models for General Time Series Forecasting
53. NeurIPS 2026Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models
54. NeurIPS 2026FOGO: Forgetting-aware Orthogonalization Optimizer
55. NeurIPS 2026Free Decompression with Algebraic Spectral Curves
56. NeurIPS 2026From Contexts to Conditionals: Statistical Self-Consistency of Persona Prompting
57. NeurIPS 2026FuncFormer: Circuit Representation Learning via the Flow of Functional Propagation
58. NeurIPS 2026General Agent Evaluation
59. NeurIPS 2026Generalizing the Geometry of Model Merging Through Fréchet Averages
60. NeurIPS 2026Geometry Matters in Packed 3D Attention
61. NeurIPS 2026GISA: A Benchmark for General Information-Seeking Assistant
62. NeurIPS 2026Global Convergence of Four-Layer Matrix Factorization under Random Initialization
63. NeurIPS 2026GPA: General Principled Framework for Linearizing Softmax Attention via KV Cache Approximation
64. NeurIPS 2026Grounded or Fabricated? Unsupervised Detection of LLM Hallucinations via Contextualized Influence on Response Embeddings
65. NeurIPS 2026Hallucination-Guided Unlearning: Using Hallucination Traces to Reveal Overfitted Memories
66. NeurIPS 2026HARC: Coupling Harmfulness and Refusal Capabilities for Robust Safety Alignment
67. NeurIPS 2026HoloGene: Learning to Lift Sliced Spatial Transcriptomics to Holistic 3D Gene Fields
68. NeurIPS 2026How Can SignSGD Outperform SGD? A Functional Scaling Law Perspective
69. NeurIPS 2026How Do Language Models Compose Functions?
70. NeurIPS 2026Hyperagents
71. NeurIPS 2026Hypergraph Representation Learning with Hyperlink Random Effects
72. NeurIPS 2026HyperTree: Scalable Unsupervised Hierarchy Discovery in Hyperbolic Space
73. NeurIPS 2026Improving General Role-Playing Agents via Psychology-Grounded Reasoning and Role-Aware Policy Optimization
74. NeurIPS 2026Indications of Belief-Guided Agency and Meta-Cognitive Monitoring in Large Language Models
75. NeurIPS 2026Inference and Uncertainty Quantification for Streaming $r$-PCA
76. NeurIPS 2026Integrating Local and Global Entropy for Uncertainty Quantification in LLMs
77. NeurIPS 2026Internal Evaluation of Unsupervised Anomaly Detection Algorithms with Explanation
78. NeurIPS 2026Intrinsic Information Theoretic Analysis of ReLU Nets
79. NeurIPS 2026Invariant Features in Language Models: Geometric Characterization and Model Attribution
80. NeurIPS 2026Inverse Linear Bandits via Linear Programs
81. NeurIPS 2026Learn from your own latents and not from tokens: A sample-complexity theory
82. NeurIPS 2026Learning a Maximum Entropy Model for Visual Textures using Diffusion
83. NeurIPS 2026Learning Augmented Exact Exponential Algorithms
84. NeurIPS 2026Learning Causal Orderings for In-Context Tabular Prediction
85. NeurIPS 2026Learning Informative Invariant Representations via Hierarchical Latent Decomposition
86. NeurIPS 2026Learning Menu-Based Mechanisms for Truthful Budget-Feasible Procurement
87. NeurIPS 2026Learning Modular Addition with Auxiliary Modulus
88. NeurIPS 2026Learning Optimal Transport Plans Via Autoregressive Token Regression
89. NeurIPS 2026Learning Orthonormal Bases for Function Spaces
90. NeurIPS 2026Learning to Bid in Repeated Second-Price Auctions with Dynamic Values and Aggregated Feedback
91. NeurIPS 2026Learning to Persuade a Biased Receiver
92. NeurIPS 2026Learning to play with spikes. Characterizing, predicting, and engineering unsupervised plasticity rules for spiking reservoir computing
93. NeurIPS 2026LIBERO-PeRM: Benchmarking Personalized Robotic Manipulation
94. NeurIPS 2026Local Sparsity Enables Unsupervised LLM Safety Detection
95. NeurIPS 2026LookWhen? Fast Video Recognition by Learning When, Where, and What to Compute
96. NeurIPS 2026Manifold Random Features
97. NeurIPS 2026MaxSketch: Robust Distinct Counting in Streams via Random Projections
98. NeurIPS 2026Measuring and Strengthening Behavioral Suppression in Language Models
99. NeurIPS 2026MedKIT: Evaluating Knowledge Integration and Generalization in Large Language Models
100. NeurIPS 2026MedVTok: A General-Purpose Medical Visual Tokenizer

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.