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

511 papers, page 7 of 11

301. NeurIPS 2024Incorporating Surrogate Gradient Norm to Improve Offline Optimization Techniques
302. NeurIPS 2024Induced Model Matching: Restricted Models Help Train Full-Featured Models
303. NeurIPS 2024Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference
304. NeurIPS 2024Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models
305. NeurIPS 2024Initializing Services in Interactive ML Systems for Diverse Users
306. NeurIPS 2024Integrating Deep Metric Learning with Coreset for Active Learning in 3D Segmentation
307. NeurIPS 2024Interventionally Consistent Surrogates for Complex Simulation Models
308. NeurIPS 2024Inversion-based Latent Bayesian Optimization
309. NeurIPS 2024IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing
310. NeurIPS 2024KFNN: K-Free Nearest Neighbor For Crowdsourcing
311. NeurIPS 2024KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantization
312. NeurIPS 2024Large Pre-trained time series models for cross-domain Time series analysis tasks
313. NeurIPS 2024Large Scale Transfer Learning for Tabular Data via Language Modeling
314. NeurIPS 2024Layer-Adaptive State Pruning for Deep State Space Models
315. NeurIPS 2024Learnability Matters: Active Learning for Video Captioning
316. NeurIPS 2024Learning Better Representations From Less Data For Propositional Satisfiability
317. NeurIPS 2024Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure
318. NeurIPS 2024Learning Formal Mathematics From Intrinsic Motivation
319. NeurIPS 2024Learning from Uncertain Data: From Possible Worlds to Possible Models
320. NeurIPS 2024Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation
321. NeurIPS 2024Learning Representations for Hierarchies with Minimal Support
322. NeurIPS 2024Learning Structure-Aware Representations of Dependent Types
323. NeurIPS 2024Learning Structured Representations with Hyperbolic Embeddings
324. NeurIPS 2024Learning the Infinitesimal Generator of Stochastic Diffusion Processes
325. NeurIPS 2024Learning to compute Gröbner bases
326. NeurIPS 2024Learning to Embed Distributions via Maximum Kernel Entropy
327. NeurIPS 2024Learning to Predict Structural Vibrations
328. NeurIPS 2024Learning Where to Edit Vision Transformers
329. NeurIPS 2024Learning-Augmented Priority Queues
330. NeurIPS 2024LLaMo: Large Language Model-based Molecular Graph Assistant
331. NeurIPS 2024LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation
332. NeurIPS 2024LLMDFA: Analyzing Dataflow in Code with Large Language Models
333. NeurIPS 2024Local Superior Soups: A Catalyst for Model Merging in Cross-Silo Federated Learning
334. NeurIPS 2024LoD-Loc: Aerial Visual Localization using LoD 3D Map with Neural Wireframe Alignment
335. NeurIPS 2024Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling
336. NeurIPS 2024MAGIS: LLM-Based Multi-Agent Framework for GitHub Issue Resolution
337. NeurIPS 2024MagR: Weight Magnitude Reduction for Enhancing Post-Training Quantization
338. NeurIPS 2024Masked Pre-training Enables Universal Zero-shot Denoiser
339. NeurIPS 2024Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
340. NeurIPS 2024MILP-StuDio: MILP Instance Generation via Block Structure Decomposition
341. NeurIPS 2024Minimum Entropy Coupling with Bottleneck
342. NeurIPS 2024Mixture of Adversarial LoRAs: Boosting Robust Generalization in Meta-Tuning
343. NeurIPS 2024Mixture of neural fields for heterogeneous reconstruction in cryo-EM
344. NeurIPS 2024Mobility-LLM: Learning Visiting Intentions and Travel Preference from Human Mobility Data with Large Language Models
345. NeurIPS 2024Model Decides How to Tokenize: Adaptive DNA Sequence Tokenization with MxDNA
346. NeurIPS 2024Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope Theory
347. NeurIPS 2024Model Sensitivity Aware Continual Learning
348. NeurIPS 2024Molecule Generation with Fragment Retrieval Augmentation
349. NeurIPS 2024MSA Generation with Seqs2Seqs Pretraining: Advancing Protein Structure Predictions
350. NeurIPS 2024MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training

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.