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 6 of 29

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
279. CVPR 2025A Bias-Free Training Paradigm for More General AI-generated Image Detection
280. CVPR 2025A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets
281. CVPR 2025A Unified Approach to Interpreting Self-supervised Pre-training Methods for 3D Point Clouds via Interactions
282. CVPR 2025A Unified Framework for Heterogeneous Semi-supervised Learning
283. CVPR 2025AeSPa : Attention-guided Self-supervised Parallel Imaging for MRI Reconstruction
284. CVPR 2025BOE-ViT: Boosting Orientation Estimation with Equivariance in Self-Supervised 3D Subtomogram Alignment
285. CVPR 2025CGMatch: A Different Perspective of Semi-supervised Learning
286. CVPR 2025CLIP-driven Coarse-to-fine Semantic Guidance for Fine-grained Open-set Semi-supervised Learning
287. CVPR 2025Common3D: Self-Supervised Learning of 3D Morphable Models for Common Objects in Neural Feature Space
288. CVPR 2025Decoupled Distillation to Erase: A General Unlearning Method for Any Class-centric Tasks
289. CVPR 2025DViN: Dynamic Visual Routing Network for Weakly Supervised Referring Expression Comprehension
290. CVPR 2025Enhancing Adversarial Transferability with Checkpoints of a Single Model's Training
291. CVPR 2025From Head to Tail: Efficient Black-box Model Inversion Attack via Long-tailed Learning
292. CVPR 2025From Prototypes to General Distributions: An Efficient Curriculum for Masked Image Modeling
293. CVPR 2025Generalized Recorrupted-to-Recorrupted: Self-Supervised Learning Beyond Gaussian Noise
294. CVPR 2025High Temporal Consistency through Semantic Similarity Propagation in Semi-Supervised Video Semantic Segmentation for Autonomous Flight
295. CVPR 2025Improve Representation for Imbalanced Regression through Geometric Constraints
296. CVPR 2025Improved Monocular Depth Prediction Using Distance Transform Over Pre-semantic Contours with Self-supervised Neural Networks
297. CVPR 2025Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement
298. CVPR 2025Improving the Transferability of Adversarial Attacks on Face Recognition with Diverse Parameters Augmentation
299. CVPR 2025Improving Transferable Targeted Attacks with Feature Tuning Mixup
300. CVPR 2025Invisible Backdoor Attack against Self-supervised Learning

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.