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

372 papers, page 7 of 8

301. NeurIPS 2025On Agnostic PAC Learning in the Small Error Regime
302. NeurIPS 2025On Reasoning Strength Planning in Large Reasoning Models
303. NeurIPS 2025On the creation of narrow AI: hierarchy and nonlocality of neural network skills
304. NeurIPS 2025On the Loss of Context Awareness in General Instruction Fine-tuning
305. NeurIPS 2025One Filters All: A Generalist Filter For State Estimation
306. NeurIPS 2025Optimistic Query Routing in Clustering-based Approximate Maximum Inner Product Search
307. NeurIPS 2025Optimizing Distributional Geometry Alignment with Optimal Transport for Generative Dataset Distillation
308. NeurIPS 2025OptiTree: Hierarchical Thoughts Generation with Tree Search for LLM Optimization Modeling
309. NeurIPS 2025PCA++: How Uniformity Induces Robustness to Background Noise in Contrastive Learning
310. NeurIPS 2025Per-Architecture Training-Free Metric Optimization for Neural Architecture Search
311. NeurIPS 2025Physics-informed machine learning with domain decomposition and global dynamics for three-dimensional intersecting flows
312. NeurIPS 2025Prediction-Powered Semi-Supervised Learning with Online Power Tuning
313. NeurIPS 2025ProSpero: Active Learning for Robust Protein Design Beyond Wild-Type Neighborhoods
314. NeurIPS 2025QCircuitBench: A Large-Scale Dataset for Benchmarking Quantum Algorithm Design
315. NeurIPS 2025Quantum Doubly Stochastic Transformers
316. NeurIPS 2025R$^2$ec: Towards Large Recommender Models with Reasoning
317. NeurIPS 2025Random Forest Autoencoders for Guided Representation Learning
318. NeurIPS 2025RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Rank Correlation between Labels
319. NeurIPS 2025Resource-Constrained Federated Continual Learning: What Does Matter?
320. NeurIPS 2025Revisiting Orbital Minimization Method for Neural Operator Decomposition
321. NeurIPS 2025RIGNO: A Graph-based Framework For Robust And Accurate Operator Learning For PDEs On Arbitrary Domains
322. NeurIPS 2025Robust Integrated Learning and Pauli Noise Mitigation for Parametrized Quantum Circuits
323. NeurIPS 2025Robust Label Proportions Learning
324. NeurIPS 2025Robust Minimax Boosting with Performance Guarantees
325. NeurIPS 2025Robust Regression of General ReLUs with Queries
326. NeurIPS 2025ROOT: Rethinking Offline Optimization as Distributional Translation via Probabilistic Bridge
327. NeurIPS 2025RSafe: Incentivizing proactive reasoning to build robust and adaptive LLM safeguards
328. NeurIPS 2025Scaling Up Active Testing to Large Language Models
329. NeurIPS 2025Self Iterative Label Refinement via Robust Unlabeled Learning
330. NeurIPS 2025Self supervised learning for in vivo localization of microelectrode arrays using raw local field potential
331. NeurIPS 2025Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
332. NeurIPS 2025Self-Supervised Selective-Guided Diffusion Model for Old-Photo Face Restoration
333. NeurIPS 2025Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
334. NeurIPS 2025SHGR: A Generalized Maximal Correlation Coefficient
335. NeurIPS 2025Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens
336. NeurIPS 2025Single-Step Operator Learning for Conditioned Time-Series Diffusion Models
337. NeurIPS 2025SMRS: advocating a unified reporting standard for surrogate models in the artificial intelligence era.
338. NeurIPS 2025Spectral Convolutional Conditional Neural Process
339. NeurIPS 2025Spectral Learning for Infinite-Horizon Average-Reward POMDPs
340. NeurIPS 2025SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
341. NeurIPS 2025Spike4DGS: Towards High-Speed Dynamic Scene Rendering with 4D Gaussian Splatting via a Spike Camera Array
342. NeurIPS 2025SpikingVTG: A Spiking Detection Transformer for Video Temporal Grounding
343. NeurIPS 2025Stability and Oracle Inequalities for Optimal Transport Maps between General Distributions
344. NeurIPS 2025Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon
345. NeurIPS 2025Stochastic Process Learning via Operator Flow Matching
346. NeurIPS 2025T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning
347. NeurIPS 2025TAPAS: Datasets for Learning the Learning with Errors Problem
348. NeurIPS 2025The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
349. NeurIPS 2025The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination
350. NeurIPS 2025The third pillar of causal analysis? A measurement perspective on causal representations

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.