General ML · supervised learning papers, 2023–2026

Key findings

• General ML · supervised learning went from 263 papers in 2023 to 279 in 2026, roughly 1.1x in three years.
• NeurIPS publishes the most General ML · supervised learning work: 731 papers from 2023 to 2026, 51% of the four-venue total.
• The fastest-growing overlap is with Diffusion Models: papers tagged with both rose from 2 in 2023 to 9 in 2026.
• Among the 6 topics under General Machine Learning, it ranks #3 by 2026 paper count; the fastest grower in the group, General ML · evaluation, is up 4.3x versus 1.1x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training
• ICML 2026$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
• ICLR 2026Adaptive Concept Discovery for Interpretable Few-Shot Text Classification
• CVPR 2026Enabling Supervised Learning of Generative Signatures for Generalized AI-Generated Images
• NeurIPS 2025$\boldsymbol{\lambda}$-Orthogonality Regularization for Compatible Representation Learning
• ICML 2025Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
• ICLR 2025Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
• CVPR 2025A Unified Framework for Heterogeneous Semi-supervised Learning
• NeurIPS 2024(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
• ICML 2024A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
• ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
• CVPR 2024Efficient Hyperparameter Optimization with Adaptive Fidelity Identification
• NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
• ICML 2023A Model-free Closeness-of-influence Test for Features in Supervised Learning
• ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
• CVPR 2023Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data
• NeurIPS 2026Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
• ICML 2026Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
• ICLR 2026Buckingham $\pi$-Invariant Test‑Time Projection for Robust PDE Surrogate Modeling
• CVPR 2026HyperNAS Enhancing Architecture Representation for NAS Predictor via Hypernetwork

All General ML · supervised learning papers

1,424 papers, page 3 of 29

101. ICML 2026Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
102. ICML 2026Continuous-Time Piecewise-Linear Recurrent Neural Networks
103. ICML 2026Contrastive Order Learning: A General Framework for Ordinal Regression
104. ICML 2026CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
105. ICML 2026Cross-View Lewis Weight Fusion Empowering Exemplar Replay for Federated Class-Incremental Learning
106. ICML 2026DART: Distribution-Aware Adaptive Relational Transfer for Adversarial Attacks against Closed-Source MLLMs
107. ICML 2026Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations
108. ICML 2026DiL: Discrete-anchored Representation Alignment for Semi-Supervised Continual Learning
109. ICML 2026Diversity-Driven Offline Multi-Objective Optimization via Nested Pareto Set Learning
110. ICML 2026Divisiveness-Consistent Label Distribution Learning
111. ICML 2026Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning
112. ICML 2026ECSEL: Explainable Classification via Signomial Equation Learning
113. ICML 2026Ekka: Automated Diagnosis of Silent Errors in LLM Inference
114. ICML 2026Enhancing Cross-subject Emotion Recognition via Heterogeneous Distribution Augmentation and Collaborative Learning
115. ICML 2026Equivariant Neural Networks for General Linear Symmetries on Lie Algebras
116. ICML 2026Euler–Poincaré Neural Dynamics: A Geometric-Mechanics Framework for Scientific Simulation
117. ICML 2026FairMerging: Rethinking Model Merging through the Lens of Fairness
118. ICML 2026Federated Data and Feature Selection by Generalized CUR Decomposition
119. ICML 2026FedReLa: Imbalanced Federated Learning via Re-Labeling
120. ICML 2026Fix the Loss, Not the Radius: Rethinking the Adversarial Perturbation of Sharpness-Aware Minimization
121. ICML 2026Flowers: A Warp Drive for Neural PDE Solvers
122. ICML 2026Fractional is Better: Learnable Derivative Orders in Neural Operator Learning
123. ICML 2026From Basis to Basis: Gaussian Particle Representation for Interpretable PDE Operators
124. ICML 2026Functional Attention: From Pairwise Affinities to Functional Correspondences
125. ICML 2026Generative Neural Operators through Diffusion Last Layer
126. ICML 2026Identifying Common Hubs in Multiple Gaussian Graphical Models
127. ICML 2026IdEst: Assessing Self-Supervised Learning Representations via Intrinsic Dimension
128. ICML 2026Impact of Connectivity on Laplacian Representations in Reinforcement Learning
129. ICML 2026Imposing Boundary Conditions on Neural Operators via Learned Function Extensions
130. ICML 2026Kronecker Generative Networks: A General Neural Architecture for Parameter-Efficient Learning Across Classification Tasks
131. ICML 2026Language Model Augmented Semi-Supervised Statistical Inference
132. ICML 2026Large Scale Manifold Balanced Clustering
133. ICML 2026LassoFlexNet: a Flexible Neural Architecture for Tabular Data
134. ICML 2026Learning Generalized Label Distributions
135. ICML 2026Learning to Emulate Chaos: Adversarial Optimal Transport Regularization
136. ICML 2026Learning to Label: A Reinforced Self-Evolving Framework for Semi-supervised Referring Expression Segmentation
137. ICML 2026Learning to Rank by Directly Optimizing Full-Order Probabilities
138. ICML 2026Learning-augmented Rent-or-Buy with a Sample
139. ICML 2026Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm
140. ICML 2026LEMUR: Learned Multi-Vector Retrieval
141. ICML 2026Lie-Algebraic Acceleration of Neural Koopman Dynamics
142. ICML 2026Likelihood over Estimation: Robust Quadratic Discriminant Analysis for Heavy-Tailed Distributions with Theory and Evidence
143. ICML 2026LOTTERY: Learning from Reference-Only Samples in Two-Sample Testing under Size Asymmetry
144. ICML 2026Low-Rank and Sparsity Are All You Need: Exploring Robust Hierarchical Latent Subspaces for Transferable Adversarial Attack
145. ICML 2026Masked Multi-path Contrast with Confidence-Gated Semantic Imputation for Incomplete Multi-view Clustering
146. ICML 2026MEC: Machine-Learning-Assisted Generalized Entropy Calibration for Semi-Supervised Mean Estimation
147. ICML 2026Mind the Budget: Accelerating Deep Reinforcement Learning using Constrained Early Exit Neural Networks
148. ICML 2026Minimizing Mismatch Risk: A Prototype-Based Routing Framework for Zero-shot LLM-generated Text Detection
149. ICML 2026MMPD-Bench: Bridging Multimodal Fission with Multi-Polarimetric Modalities Decomposition
150. ICML 2026Multi-Scale Wavelet Transformers for Operator Learning of Dynamical Systems

FAQ

How many General ML · supervised learning papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

1,425 in total: 263 in 2023, 511 in 2024, 372 in 2025, 279 in 2026.

How many General ML · supervised learning papers are at NeurIPS 2026?

NeurIPS 2026 has 87 General ML · supervised learning papers, versus 171 the year before.

How many General ML · supervised learning papers are at ICLR 2026?

ICLR 2026 has 48 General ML · supervised learning papers, versus 40 the year before.

How many General ML · supervised learning papers are at ICML 2026?

ICML 2026 has 111 General ML · supervised learning papers, versus 114 the year before.

How many General ML · supervised learning papers are at CVPR 2026?

CVPR 2026 has 33 General ML · supervised learning papers, versus 47 the year before.

Which conference publishes the most General ML · supervised learning papers?

NeurIPS, with 731 papers from 2023 to 2026.