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

278 papers, page 6 of 6

251. NeurIPS 2026Saddle-to-Saddle Dynamics in Self-Supervised Shortcut Learning
252. NeurIPS 2026Safe Linear Bandits with Unknown Safety Gaps
253. NeurIPS 2026Sample Efficient Generative Molecular Optimization with Joint Self-Improvement
254. NeurIPS 2026Seeing but Not Detecting: Privacy-Preserving Scene Text Attack via Hybrid Adversarial Policy Learning
255. NeurIPS 2026Self-Distillation of Hidden Layers for Masked Self-Supervised Representation Learning
256. NeurIPS 2026Self-Supervised Doppler-Guided RF Odometry
257. NeurIPS 2026SetAD: Semi-Supervised Anomaly Learning in Contextual Sets
258. NeurIPS 2026SIEVE: Overcoming Topological Obstruction in Equivariant Self-Supervised Learning
259. NeurIPS 2026Sparsely Supervised Diffusion
260. NeurIPS 2026SPDEBench: An Extensive Benchmark for Learning Stochastic PDEs
261. NeurIPS 2026SS3D: End2End Self-Supervised 3D from Web Videos
262. NeurIPS 2026StarWM: Self-Supervised Trained Attention Routing for Robust World Models
263. NeurIPS 2026Sup-Norm Error under Proportional Asymptotics: Phase Transitions under Linear Regression
264. NeurIPS 2026Surrogate Calibration for Transferable Adversarial Attacks against Black-Box MLLMs
265. NeurIPS 2026Testable Learning of General Halfspaces under Massart Noise
266. NeurIPS 2026The Graph Concept Bottleneck: Decoding Combinatorial Reasoning in GNNs for Interpretability
267. NeurIPS 2026The Platonic Defense: Backdoor Defense for Self-Supervised Encoders in the Era of Large Scale Pre-training
268. NeurIPS 2026Theory Guided and Interpretable Neural Operator Design for Partial Differential Equation Learning
269. NeurIPS 2026Topology-Aware Representation Alignment for Semi-Supervised Vision-Language Learning
270. NeurIPS 2026Train on the Sphere, Deploy on the Hill: Closed-Form-Anchored Surrogates for Real-Terrain Boundary-Integral Equations
271. NeurIPS 2026Trajectory-Matching Meta Pseudo-Labeling for Semi-Supervised Learning
272. NeurIPS 2026Transferable, Time-Parallel Graph Dynamics via Space-Time Factorization
273. NeurIPS 2026Tree-Structured Synergy of Large Language Models and Bayesian Optimization for Efficient CASH
274. NeurIPS 2026Tune-Up Open-Weight CLIP: Optimization Framework for Self-Supervised Fine-tuning of CLIP
275. NeurIPS 2026TurtLES: A Large-Scale Benchmark for Turbulent 3D Neural PDE Surrogates
276. NeurIPS 2026What to Perturb, How to Propagate: A Graph-Guided Transferable Attack on VLP Models
277. NeurIPS 2026Winning Lottery Tickets in Neural Networks via a Quantum-Inspired Classical Algorithm
278. NeurIPS 2026ZNO: Stable Rational Neural Operators in the Z-Domain for Discrete-Time Dynamics

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.