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

798 papers, page 3 of 16

101. ICLR 2026Context and Diversity Matter: The Emergence of In-Context Learning in World Models
102. ICLR 2026Contrastive Predictive Coding Done Right for Mutual Information Estimation
103. ICLR 2026Convergence Analysis of Tsetlin Machines under Noise-Free and Noisy Training Conditions: from $2$ Bits to $k$ Bits
104. ICLR 2026Convergence of Regret Matching in Potential Games and Constrained Optimization
105. ICLR 2026Convergent Differential Privacy Analysis for General Federated Learning
106. ICLR 2026COSMO-INR: Complex Sinusoidal Modulation for Implicit Neural Representations
107. ICLR 2026Cross-Domain Lossy Compression via Rate- and Classification-Constrained Optimal Transport
108. ICLR 2026CSRv2: Unlocking Ultra-Sparse Embeddings
109. ICLR 2026CUPID: A Plug-in Framework for Joint Aleatoric and Epistemic Uncertainty Estimation with a Single Model
110. ICLR 2026Curse of Slicing: Why Sliced Mutual Information is a Deceptive Measure of Statistical Dependence
111. ICLR 2026DAVE: A VLM Vision Encoder for Document Understanding and Web Agents
112. ICLR 2026Debiased and Denoised Projection Learning for Incomplete Multi-view Clustering
113. ICLR 2026Debugging Concept Bottleneck Models through Removal and Retraining
114. ICLR 2026Decomposing Representation Space into Interpretable Subspaces with Unsupervised Learning
115. ICLR 2026Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement
116. ICLR 2026Decoupling Positional and Symbolic Attention in Transformers
117. ICLR 2026Decoupling the Class Label and the Target Concept in Machine Unlearning
118. ICLR 2026DeepFRC: An End-to-End Deep Learning Model for Functional Registration and Classification
119. ICLR 2026Difference Predictive Coding for Training Spiking Neural Networks
120. ICLR 2026Differentiable Lifting for Topological Neural Networks
121. ICLR 2026Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
122. ICLR 2026DiffSDA: Unsupervised Diffusion Sequential Disentanglement Across Modalities
123. ICLR 2026Discrete Compositional Generation via General Soft Operators and Robust Reinforcement Learning
124. ICLR 2026Disentangled representation learning through unsupervised symmetry group discovery
125. ICLR 2026Distributionally Robust Classification for Multi-source Unsupervised Domain Adaptation
126. ICLR 2026DiVeQ: Differentiable Vector Quantization Using the Reparameterization Trick
127. ICLR 2026Diverse Dictionary Learning
128. ICLR 2026Don't Forget Its Variance! The Minimum Path Variance Principle for Accurate and Stable Score-Based Models
129. ICLR 2026Dual Perspectives on Non-Contrastive Self-Supervised Learning
130. ICLR 2026Dual-Branch Representations with Dynamic Gated Fusion and Triple-Granularity Alignment for Deep Multi-View Clustering
131. ICLR 2026Einstein Fields: A Neural Perspective To Computational General Relativity
132. ICLR 2026Error Feedback for Muon and Friends
133. ICLR 2026Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking
134. ICLR 2026Explainable $ K $-means Neural Networks for Multi-view Clustering
135. ICLR 2026Fairness via Independence: A General Regularization Framework for Machine Learning
136. ICLR 2026FeDaL: Federated Dataset Learning for General Time Series Foundation Models
137. ICLR 2026Federated Graph-Level Clustering Network with Dual Knowledge Separation
138. ICLR 2026FedOpenMatch: Towards Semi-Supervised Federated Learning in Open-Set Environments
139. ICLR 2026Fine-Grained Class-Conditional Distribution Balancing for Debiased Learning
140. ICLR 2026FlyPrompt: Brain-Inspired Random-Expanded Routing with Temporal-Ensemble Experts for General Continual Learning
141. ICLR 2026Fore-Mamba3D: Mamba-based Foreground-Enhanced Encoding for 3D Object Detection
142. ICLR 2026From Parameters to Behaviors: Unsupervised Compression of the Policy Space
143. ICLR 2026From Seeing to Doing: Bridging Reasoning and Decision for Robotic Manipulation
144. ICLR 2026From Vicious to Virtuous Cycles: Synergistic Representation Learning for Unsupervised Video Object-Centric Learning
145. ICLR 2026FS-KAN: Permutation Equivariant Kolmogorov-Arnold Networks via Function Sharing
146. ICLR 2026Gauge Flow Matching: Efficient Constrained Generative Modeling over General Convex Set and Beyond
147. ICLR 2026General Exploratory Bonus for Optimistic Exploration in RLHF
148. ICLR 2026General search techniques without common knowledge for imperfect-information games, and application to superhuman Fog of War chess
149. ICLR 2026Generalization Below the Edge of Stability: The Role of Data Geometry
150. ICLR 2026Generalizing Linear Autoencoder Recommenders with Decoupled Expected Quadratic Loss

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.