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 10 of 11

451. NeurIPS 2024ST$_k$: A Scalable Module for Solving Top-k Problems
452. NeurIPS 2024STONE: A Submodular Optimization Framework for Active 3D Object Detection
453. NeurIPS 2024Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
454. NeurIPS 2024Structural Inference of Dynamical Systems with Conjoined State Space Models
455. NeurIPS 2024Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics
456. NeurIPS 2024Suitable is the Best: Task-Oriented Knowledge Fusion in Vulnerability Detection
457. NeurIPS 2024Supervised Kernel Thinning
458. NeurIPS 2024Synthetic Programming Elicitation for Text-to-Code in Very Low-Resource Programming and Formal Languages
459. NeurIPS 2024TabEBM: A Tabular Data Augmentation Method with Distinct Class-Specific Energy-Based Models
460. NeurIPS 2024TAIA: Large Language Models are Out-of-Distribution Data Learners
461. NeurIPS 2024Task-Agnostic Machine-Learning-Assisted Inference
462. NeurIPS 2024Task-oriented Time Series Imputation Evaluation via Generalized Representers
463. NeurIPS 2024Textual Training for the Hassle-Free Removal of Unwanted Visual Data: Case Studies on OOD and Hateful Image Detection
464. NeurIPS 2024The ALCHEmist: Automated Labeling 500x CHEaper than LLM Data Annotators
465. NeurIPS 2024The Impact of Initialization on LoRA Finetuning Dynamics
466. NeurIPS 2024The Importance of Being Scalable: Improving the Speed and Accuracy of Neural Network Interatomic Potentials Across Chemical Domains
467. NeurIPS 2024The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks
468. NeurIPS 2024The Power of Hard Attention Transformers on Data Sequences: A formal language theoretic perspective
469. NeurIPS 2024The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
470. NeurIPS 2024Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning
471. NeurIPS 2024Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting
472. NeurIPS 2024Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models
473. NeurIPS 2024Topological Hidden Markov Models
474. NeurIPS 2024Toward a Stable, Fair, and Comprehensive Evaluation of Object Hallucination in Large Vision-Language Models
475. NeurIPS 2024Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning
476. NeurIPS 2024Towards Accurate and Fair Cognitive Diagnosis via Monotonic Data Augmentation
477. NeurIPS 2024Towards Diverse Device Heterogeneous Federated Learning via Task Arithmetic Knowledge Integration
478. NeurIPS 2024Towards General Loop Invariant Generation: A Benchmark of Programs with Memory Manipulation
479. NeurIPS 2024Towards Next-Generation Logic Synthesis: A Scalable Neural Circuit Generation Framework
480. NeurIPS 2024Towards Stable Representations for Protein Interface Prediction
481. NeurIPS 2024Towards training digitally-tied analog blocks via hybrid gradient computation
482. NeurIPS 2024Towards Understanding Evolving Patterns in Sequential Data
483. NeurIPS 2024Training Compute-Optimal Protein Language Models
484. NeurIPS 2024Transductive Active Learning: Theory and Applications
485. NeurIPS 2024Transferable Adversarial Attacks on SAM and Its Downstream Models
486. NeurIPS 2024TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks
487. NeurIPS 2024UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization Problems
488. NeurIPS 2024Ultrafast classical phylogenetic method beats large protein language models on variant effect prediction
489. NeurIPS 2024Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective
490. NeurIPS 2024UniIF: Unified Molecule Inverse Folding
491. NeurIPS 2024Universal Physics Transformers: A Framework For Efficiently Scaling Neural Operators
492. NeurIPS 2024Universal Sample Coding
493. NeurIPS 2024Unlocking the Potential of Global Human Expertise
494. NeurIPS 2024UnSeg: One Universal Unlearnable Example Generator is Enough against All Image Segmentation
495. NeurIPS 2024Unsupervised Anomaly Detection in The Presence of Missing Values
496. NeurIPS 2024Unsupervised Discovery of Formulas for Mathematical Constants
497. NeurIPS 2024Untrained Neural Nets for Snapshot Compressive Imaging: Theory and Algorithms
498. NeurIPS 2024Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?
499. NeurIPS 2024Unveiling The Matthew Effect Across Channels: Assessing Layer Width Sufficiency via Weight Norm Variance
500. NeurIPS 2024UQE: A Query Engine for Unstructured Databases

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.