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 13 of 29

601. NeurIPS 2025Robust Label Proportions Learning
602. NeurIPS 2025Robust Minimax Boosting with Performance Guarantees
603. NeurIPS 2025Robust Regression of General ReLUs with Queries
604. NeurIPS 2025ROOT: Rethinking Offline Optimization as Distributional Translation via Probabilistic Bridge
605. NeurIPS 2025RSafe: Incentivizing proactive reasoning to build robust and adaptive LLM safeguards
606. NeurIPS 2025Scaling Up Active Testing to Large Language Models
607. NeurIPS 2025Self Iterative Label Refinement via Robust Unlabeled Learning
608. NeurIPS 2025Self supervised learning for in vivo localization of microelectrode arrays using raw local field potential
609. NeurIPS 2025Self-Supervised Contrastive Learning is Approximately Supervised Contrastive Learning
610. NeurIPS 2025Self-Supervised Selective-Guided Diffusion Model for Old-Photo Face Restoration
611. NeurIPS 2025Semi-Supervised Regression with Heteroscedastic Pseudo-Labels
612. NeurIPS 2025SHGR: A Generalized Maximal Correlation Coefficient
613. NeurIPS 2025Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens
614. NeurIPS 2025Single-Step Operator Learning for Conditioned Time-Series Diffusion Models
615. NeurIPS 2025SMRS: advocating a unified reporting standard for surrogate models in the artificial intelligence era.
616. NeurIPS 2025Spectral Convolutional Conditional Neural Process
617. NeurIPS 2025Spectral Learning for Infinite-Horizon Average-Reward POMDPs
618. NeurIPS 2025SPFL: Sequential updates with Parallel aggregation for Enhanced Federated Learning under Category and Domain Shifts
619. NeurIPS 2025Spike4DGS: Towards High-Speed Dynamic Scene Rendering with 4D Gaussian Splatting via a Spike Camera Array
620. NeurIPS 2025SpikingVTG: A Spiking Detection Transformer for Video Temporal Grounding
621. NeurIPS 2025Stability and Oracle Inequalities for Optimal Transport Maps between General Distributions
622. NeurIPS 2025Stable Minima of ReLU Neural Networks Suffer from the Curse of Dimensionality: The Neural Shattering Phenomenon
623. NeurIPS 2025Stochastic Process Learning via Operator Flow Matching
624. NeurIPS 2025T-REGS: Minimum Spanning Tree Regularization for Self-Supervised Learning
625. NeurIPS 2025TAPAS: Datasets for Learning the Learning with Errors Problem
626. NeurIPS 2025The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
627. NeurIPS 2025The Power of Iterative Filtering for Supervised Learning with (Heavy) Contamination
628. NeurIPS 2025The third pillar of causal analysis? A measurement perspective on causal representations
629. NeurIPS 2025Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
630. NeurIPS 2025Think before Recommendation: Autonomous Reasoning-enhanced Recommender
631. NeurIPS 2025Thumb on the Scale: Optimal Loss Weighting in Last Layer Retraining
632. NeurIPS 2025TITAN: A Trajectory-Informed Technique for Adaptive Parameter Freezing in Large-Scale VQE
633. NeurIPS 2025Towards a General Attention Framework on Gyrovector Spaces for Matrix Manifolds
634. NeurIPS 2025Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs
635. NeurIPS 2025Towards Visualization-of-Thought Jailbreak Attack against Large Visual Language Models
636. NeurIPS 2025Train on Pins and Test on Obstacles for Rectilinear Steiner Minimum Tree
637. NeurIPS 2025TransferBench: Benchmarking Ensemble-based Black-box Transfer Attacks
638. NeurIPS 2025TRiCo: Triadic Game-Theoretic Co-Training for Robust Semi-Supervised Learning
639. NeurIPS 2025True Zero-Shot Inference of Dynamical Systems Preserving Long-Term Statistics
640. NeurIPS 2025Uncertainty-Aware Multi-Objective Reinforcement Learning-Guided Diffusion Models for 3D De Novo Molecular Design
641. NeurIPS 2025Uncertainty-Informed Meta Pseudo Labeling for Surrogate Modeling with Limited Labeled Data
642. NeurIPS 2025Understanding Contrastive Learning via Gaussian Mixture Models
643. NeurIPS 2025UniMRSeg: Unified Modality-Relax Segmentation via Hierarchical Self-Supervised Compensation
644. NeurIPS 2025Variational Supervised Contrastive Learning
645. NeurIPS 2025Vertical Federated Feature Screening
646. NeurIPS 2025ViSPLA: Visual Iterative Self-Prompting for Language-Guided 3D Affordance Learning
647. NeurIPS 2025What Do Latent Action Models Actually Learn?
648. NeurIPS 2025What Does It Take to Build a Performant Selective Classifier?
649. NeurIPS 2025When No Paths Lead to Rome: Benchmarking Systematic Neural Relational Reasoning
650. NeurIPS 2025WolBanking77: Wolof Banking Speech Intent Classification Dataset

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.