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 6 of 7

251. ICML 2024In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
252. ICML 2024Information Flow in Self-Supervised Learning
253. ICML 2024Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
254. ICML 2024MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
255. ICML 2024Neural Operators with Localized Integral and Differential Kernels
256. ICML 2024OTMatch: Improving Semi-Supervised Learning with Optimal Transport
257. ICML 2024OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
258. ICML 2024Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
259. ICML 2024Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
260. ICML 2024Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation
261. ICML 2024Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation
262. ICML 2024Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
263. ICML 2024SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification
264. ICML 2024Towards Realistic Model Selection for Semi-supervised Learning
265. ICML 2024Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation
266. ICML 2024Unveiling the Dynamics of Information Interplay in Supervised Learning
267. ICML 2024UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
268. ICML 2024Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
269. ICML 2024Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
270. ICML 2023A Model-free Closeness-of-influence Test for Features in Supervised Learning
271. ICML 2023A Neural PDE Solver with Temporal Stencil Modeling
272. ICML 2023Active Ranking of Experts Based on their Performances in Many Tasks
273. ICML 2023Analyzing Privacy Leakage in Machine Learning via Multiple Hypothesis Testing: A Lesson From Fano
274. ICML 2023AutoCoreset: An Automatic Practical Coreset Construction Framework
275. ICML 2023Bidirectional Adaptation for Robust Semi-Supervised Learning with Inconsistent Data Distributions
276. ICML 2023Continual Learners are Incremental Model Generalizers
277. ICML 2023CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations
278. ICML 2023Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least
279. ICML 2023Dimensionality Reduction for General KDE Mode Finding
280. ICML 2023Disentangled Multi-Fidelity Deep Bayesian Active Learning
281. ICML 2023Distance Weighted Supervised Learning for Offline Interaction Data
282. ICML 2023Evaluating Self-Supervised Learning via Risk Decomposition
283. ICML 2023Fast Sampling of Diffusion Models via Operator Learning
284. ICML 2023Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods
285. ICML 2023GNOT: A General Neural Operator Transformer for Operator Learning
286. ICML 2023Image Shortcut Squeezing: Countering Perturbative Availability Poisons with Compression
287. ICML 2023Learning Neural PDE Solvers with Parameter-Guided Channel Attention
288. ICML 2023Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
289. ICML 2023Loss Balancing for Fair Supervised Learning
290. ICML 2023Machine Learning Force Fields with Data Cost Aware Training
291. ICML 2023Minimizing Trajectory Curvature of ODE-based Generative Models
292. ICML 2023Neural Inverse Operators for Solving PDE Inverse Problems
293. ICML 2023Neural Status Registers
294. ICML 2023Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization
295. ICML 2023NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data
296. ICML 2023On the Stepwise Nature of Self-Supervised Learning
297. ICML 2023Optimizing Hyperparameters with Conformal Quantile Regression
298. ICML 2023Random Teachers are Good Teachers
299. ICML 2023RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank
300. ICML 2023Sample Complexity of Probability Divergences under Group Symmetry

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.