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 21 of 29

1001. NeurIPS 2024Multi-Instance Partial-Label Learning with Margin Adjustment
1002. NeurIPS 2024Multi-Label Open Set Recognition
1003. NeurIPS 2024Multi-language Diversity Benefits Autoformalization
1004. NeurIPS 2024Multi-modal Transfer Learning between Biological Foundation Models
1005. NeurIPS 2024Multiple Physics Pretraining for Spatiotemporal Surrogate Models
1006. NeurIPS 2024Mutli-Armed Bandits with Network Interference
1007. NeurIPS 2024Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits
1008. NeurIPS 2024Nearly Optimal Approximation of Matrix Functions by the Lanczos Method
1009. NeurIPS 2024Neglected Hessian component explains mysteries in sharpness regularization
1010. NeurIPS 2024Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization
1011. NeurIPS 2024Neural Conditional Probability for Uncertainty Quantification
1012. NeurIPS 2024Neural Cover Selection for Image Steganography
1013. NeurIPS 2024Neural Krylov Iteration for Accelerating Linear System Solving
1014. NeurIPS 2024Neural Model Checking
1015. NeurIPS 2024Neural P$^3$M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
1016. NeurIPS 2024NeuralFuse: Learning to Recover the Accuracy of Access-Limited Neural Network Inference in Low-Voltage Regimes
1017. NeurIPS 2024NeuralSteiner: Learning Steiner Tree for Overflow-avoiding Global Routing in Chip Design
1018. NeurIPS 2024Neuronal Competition Groups with Supervised STDP for Spike-Based Classification
1019. NeurIPS 2024Newton Informed Neural Operator for Solving Nonlinear Partial Differential Equations
1020. NeurIPS 2024NoMAD-Attention: Efficient LLM Inference on CPUs Through Multiply-add-free Attention
1021. NeurIPS 2024Non-parametric classification via expand-and-sparsify representation
1022. NeurIPS 2024Nonparametric Evaluation of Noisy ICA Solutions
1023. NeurIPS 2024Off-Policy Selection for Initiating Human-Centric Experimental Design
1024. NeurIPS 2024On Softmax Direct Preference Optimization for Recommendation
1025. NeurIPS 2024On the Comparison between Multi-modal and Single-modal Contrastive Learning
1026. NeurIPS 2024On the Complexity of Teaching a Family of Linear Behavior Cloning Learners
1027. NeurIPS 2024On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
1028. NeurIPS 2024On Weak Regret Analysis for Dueling Bandits
1029. NeurIPS 2024One-shot Federated Learning via Synthetic Distiller-Distillate Communication
1030. NeurIPS 2024Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
1031. NeurIPS 2024Optimal deep learning of holomorphic operators between Banach spaces
1032. NeurIPS 2024Optimal Design for Human Preference Elicitation
1033. NeurIPS 2024OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
1034. NeurIPS 2024PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
1035. NeurIPS 2024Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
1036. NeurIPS 2024Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics
1037. NeurIPS 2024Pearls from Pebbles: Improved Confidence Functions for Auto-labeling
1038. NeurIPS 2024Persistent Homology for High-dimensional Data Based on Spectral Methods
1039. NeurIPS 2024Persistent Test-time Adaptation in Recurring Testing Scenarios
1040. NeurIPS 2024Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
1041. NeurIPS 2024Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning
1042. NeurIPS 2024PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation
1043. NeurIPS 2024Piecewise deterministic generative models
1044. NeurIPS 2024Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction
1045. NeurIPS 2024Posture-Informed Muscular Force Learning for Robust Hand Pressure Estimation
1046. NeurIPS 2024PowerPM: Foundation Model for Power Systems
1047. NeurIPS 2024Predicting Label Distribution from Ternary Labels
1048. NeurIPS 2024Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization
1049. NeurIPS 2024Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors
1050. NeurIPS 2024Progressive Entropic Optimal Transport Solvers

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.