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

731 papers, page 11 of 15

501. NeurIPS 2024One-shot Federated Learning via Synthetic Distiller-Distillate Communication
502. NeurIPS 2024Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
503. NeurIPS 2024Optimal deep learning of holomorphic operators between Banach spaces
504. NeurIPS 2024Optimal Design for Human Preference Elicitation
505. NeurIPS 2024OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
506. NeurIPS 2024PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices
507. NeurIPS 2024Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting
508. NeurIPS 2024Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics
509. NeurIPS 2024Pearls from Pebbles: Improved Confidence Functions for Auto-labeling
510. NeurIPS 2024Persistent Homology for High-dimensional Data Based on Spectral Methods
511. NeurIPS 2024Persistent Test-time Adaptation in Recurring Testing Scenarios
512. NeurIPS 2024Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models
513. NeurIPS 2024Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning
514. NeurIPS 2024PhyloGen: Language Model-Enhanced Phylogenetic Inference via Graph Structure Generation
515. NeurIPS 2024Piecewise deterministic generative models
516. NeurIPS 2024Pin-Tuning: Parameter-Efficient In-Context Tuning for Few-Shot Molecular Property Prediction
517. NeurIPS 2024Posture-Informed Muscular Force Learning for Robust Hand Pressure Estimation
518. NeurIPS 2024PowerPM: Foundation Model for Power Systems
519. NeurIPS 2024Predicting Label Distribution from Ternary Labels
520. NeurIPS 2024Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization
521. NeurIPS 2024Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priors
522. NeurIPS 2024Progressive Entropic Optimal Transport Solvers
523. NeurIPS 2024ProSST: Protein Language Modeling with Quantized Structure and Disentangled Attention
524. NeurIPS 2024Protein-Nucleic Acid Complex Modeling with Frame Averaging Transformer
525. NeurIPS 2024ProtGO: Function-Guided Protein Modeling for Unified Representation Learning
526. NeurIPS 2024Provable and Efficient Dataset Distillation for Kernel Ridge Regression
527. NeurIPS 2024Proving Theorems Recursively
528. NeurIPS 2024PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation
529. NeurIPS 2024QTIP: Quantization with Trellises and Incoherence Processing
530. NeurIPS 2024Quantum algorithm for large-scale market equilibrium computation
531. NeurIPS 2024Random Cycle Coding: Lossless Compression of Cluster Assignments via Bits-Back Coding
532. NeurIPS 2024RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier
533. NeurIPS 2024Real-Time Selection Under General Constraints via Predictive Inference
534. NeurIPS 2024Reasoning Multi-Agent Behavioral Topology for Interactive Autonomous Driving
535. NeurIPS 2024REDUCR: Robust Data Downsampling using Class Priority Reweighting
536. NeurIPS 2024Referencing Where to Focus: Improving Visual Grounding with Referential Query
537. NeurIPS 2024Reinforcement Learning Guided Semi-Supervised Learning
538. NeurIPS 2024ReMAP: Neural Model Reprogramming with Network Inversion and Retrieval-Augmented Mapping for Adaptive Motion Forecasting
539. NeurIPS 2024Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design
540. NeurIPS 2024Reshuffling Resampling Splits Can Improve Generalization of Hyperparameter Optimization
541. NeurIPS 2024Resource-Aware Federated Self-Supervised Learning with Global Class Representations
542. NeurIPS 2024Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective
543. NeurIPS 2024Retrieval-Retro: Retrieval-based Inorganic Retrosynthesis with Expert Knowledge
544. NeurIPS 2024Revisiting Ensembling in One-Shot Federated Learning
545. NeurIPS 2024Revisiting K-mer Profile for Effective and Scalable Genome Representation Learning
546. NeurIPS 2024Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective
547. NeurIPS 2024Road Network Representation Learning with the Third Law of Geography
548. NeurIPS 2024Robust Contrastive Multi-view Clustering against Dual Noisy Correspondence
549. NeurIPS 2024Robust Offline Active Learning on Graphs
550. NeurIPS 2024Safe Time-Varying Optimization based on Gaussian Processes with Spatio-Temporal Kernel

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.