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

375 papers, page 5 of 8

201. NeurIPS 2024MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization
202. NeurIPS 2024Masked Pre-training Enables Universal Zero-shot Denoiser
203. NeurIPS 2024Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
204. NeurIPS 2024MILP-StuDio: MILP Instance Generation via Block Structure Decomposition
205. NeurIPS 2024Minimum Entropy Coupling with Bottleneck
206. NeurIPS 2024Mixture of Adversarial LoRAs: Boosting Robust Generalization in Meta-Tuning
207. NeurIPS 2024Mixture of neural fields for heterogeneous reconstruction in cryo-EM
208. NeurIPS 2024Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models
209. NeurIPS 2024Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA
210. NeurIPS 2024Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory
211. NeurIPS 2024Model Sensitivity Aware Continual Learning
212. NeurIPS 2024Molecule Generation with Fragment Retrieval Augmentation
213. NeurIPS 2024MSA Generation with Seqs2Seqs Pretraining: Advancing Protein Structure Predictions
214. NeurIPS 2024MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
215. NeurIPS 2024Multi-Instance Partial-Label Learning with Margin Adjustment
216. NeurIPS 2024Multi-Label Open Set Recognition
217. NeurIPS 2024Multi-language Diversity Benefits Autoformalization
218. NeurIPS 2024Multi-modal Transfer Learning between Biological Foundation Models
219. NeurIPS 2024Multiple Physics Pretraining for Spatiotemporal Surrogate Models
220. NeurIPS 2024Mutli-Armed Bandits with Network Interference
221. NeurIPS 2024Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits
222. NeurIPS 2024Nearly Optimal Approximation of Matrix Functions by the Lanczos Method
223. NeurIPS 2024Neglected Hessian component explains mysteries in sharpness regularization
224. NeurIPS 2024Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization
225. NeurIPS 2024Neural Conditional Probability for Uncertainty Quantification
226. NeurIPS 2024Neural Cover Selection for Image Steganography
227. NeurIPS 2024Neural Krylov Iteration for Accelerating Linear System Solving
228. NeurIPS 2024Neural Model Checking
229. NeurIPS 2024Neural P$^3$M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
230. NeurIPS 2024NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes
231. NeurIPS 2024NeuralSteiner: Learning Steiner Tree for Overflow-avoiding Global Routing in Chip Design
232. NeurIPS 2024Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
233. NeurIPS 2024Newton Informed Neural Operator for Solving Nonlinear Partial Differential Equations
234. NeurIPS 2024NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention
235. NeurIPS 2024Non-parametric classification via expand-and-sparsify representation
236. NeurIPS 2024Nonparametric Evaluation of Noisy ICA Solutions
237. NeurIPS 2024Off-Policy Selection for Initiating Human-Centric Experimental Design
238. NeurIPS 2024On Softmax Direct Preference Optimization for Recommendation
239. NeurIPS 2024On the Comparison between Multi-modal and Single-modal Contrastive Learning
240. NeurIPS 2024On the Complexity of Teaching a Family of Linear Behavior Cloning Learners
241. NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
242. NeurIPS 2024On Weak Regret Analysis for Dueling Bandits
243. NeurIPS 2024One-shot Federated Learning via Synthetic Distiller-Distillate Communication
244. NeurIPS 2024Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
245. NeurIPS 2024Optimal deep learning of holomorphic operators between Banach spaces
246. NeurIPS 2024Optimal Design for Human Preference Elicitation
247. NeurIPS 2024OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
248. NeurIPS 2024PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
249. NeurIPS 2024Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
250. NeurIPS 2024Partial observation can induce mechanistic mismatches in data-constrained models of neural 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.