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

313 papers, page 5 of 7

201. ICML 2025SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
202. ICML 2025SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning
203. ICML 2025Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum
204. ICML 2025Self-Supervised Transformers as Iterative Solution Improvers for Constraint Satisfaction
205. ICML 2025Shifting Time: Time-series Forecasting with Khatri-Rao Neural Operators
206. ICML 2025Simplifying DINO via Coding Rate Regularization
207. ICML 2025Spherical Rotation Dimension Reduction with Geometric Loss Functions
208. ICML 2025Stabilizing Sample Similarity in Representation via Mitigating Random Consistency
209. ICML 2025Stray Intrusive Outliers-Based Feature Selection on Intra-Class Asymmetric Instance Distribution or Multiple High-Density Clusters
210. ICML 2025Survival Analysis via Density Estimation
211. ICML 2025Tensorized Multi-View Multi-Label Classification via Laplace Tensor Rank
212. ICML 2025Testing Conditional Mean Independence Using Generative Neural Networks
213. ICML 2025Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos
214. ICML 2025TLLC: Transfer Learning-based Label Completion for Crowdsourcing
215. ICML 2025Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification
216. ICML 2025Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift
217. ICML 2025TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree
218. ICML 2025Trusted Multi-View Classification with Expert Knowledge Constraints
219. ICML 2025Unbiased Recommender Learning from Implicit Feedback via Weakly Supervised Learning
220. ICML 2025Understanding Model Ensemble in Transferable Adversarial Attack
221. ICML 2025Understanding the Unfairness in Network Quantization
222. ICML 2025Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
223. ICML 2025Weakly Supervised Anomaly Detection via Dual-Tailed Kernel
224. ICML 2025Weakly-Supervised Contrastive Learning for Imprecise Class Labels
225. ICML 2025X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
226. ICML 2024A General Framework for Learning from Weak Supervision
227. ICML 2024A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
228. ICML 2024A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
229. ICML 2024A3S: A General Active Clustering Method with Pairwise Constraints
230. ICML 2024Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning
231. ICML 2024Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning
232. ICML 2024Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
233. ICML 2024Boosting Offline Optimizers with Surrogate Sensitivity
234. ICML 2024Bootstrap AutoEncoders With Contrastive Paradigm for Self-supervised Gaze Estimation
235. ICML 2024Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach
236. ICML 2024Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
237. ICML 2024ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
238. ICML 2024Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning
239. ICML 2024Counterfactual Metarules for Local and Global Recourse
240. ICML 2024Deep Stochastic Mechanics
241. ICML 2024Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
242. ICML 2024Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
243. ICML 2024Equivariant Graph Neural Operator for Modeling 3D Dynamics
244. ICML 2024Exploring Correlations of Self-Supervised Tasks for Graphs
245. ICML 2024FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data
246. ICML 2024From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble
247. ICML 2024Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution
248. ICML 2024High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
249. ICML 2024Implicit Representations via Operator Learning
250. ICML 2024Improved Operator Learning by Orthogonal Attention

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.