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

171 papers, page 4 of 4

151. NeurIPS 2025Think before Recommendation: Autonomous Reasoning-enhanced Recommender
152. NeurIPS 2025Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining
153. NeurIPS 2025TITAN: A Trajectory-Informed Technique for Adaptive Parameter Freezing in Large-Scale VQE
154. NeurIPS 2025Towards a General Attention Framework on Gyrovector Spaces for Matrix Manifolds
155. NeurIPS 2025Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
156. NeurIPS 2025Towards Visualization-of-Thought Jailbreak Attack against Large Visual Language Models
157. NeurIPS 2025Train on Pins and Test on Obstacles for Rectilinear Steiner Minimum Tree
158. NeurIPS 2025TransferBench: Benchmarking Ensemble-based Black-box Transfer Attacks
159. NeurIPS 2025TRiCo: Triadic Game-Theoretic Co-Training for Robust Semi-Supervised Learning
160. NeurIPS 2025True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics
161. NeurIPS 2025Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design
162. NeurIPS 2025Uncertainty-Informed Meta Pseudo Labeling for Surrogate Modeling with Limited Labeled Data
163. NeurIPS 2025Understanding Contrastive Learning via Gaussian Mixture Models
164. NeurIPS 2025UniMRSeg: Unified Modality-Relax Segmentation via Hierarchical Self-Supervised Compensation
165. NeurIPS 2025Variational Supervised Contrastive Learning
166. NeurIPS 2025Vertical Federated Feature Screening
167. NeurIPS 2025ViSPLA: Visual Iterative Self-Prompting for Language-Guided 3D Affordance Learning
168. NeurIPS 2025What Do Latent Action Models Actually Learn?
169. NeurIPS 2025What Does It Take to Build a Performant Selective Classifier?
170. NeurIPS 2025When No Paths Lead to Rome: Benchmarking Systematic Neural Relational Reasoning
171. NeurIPS 2025WolBanking77: Wolof Banking Speech Intent Classification Dataset

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.