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

48 papers, page 1 of 1

1. ICLR 2026Adaptive Acquisition Selection for Bayesian Optimization with Large Language Models
2. ICLR 2026Adaptive Concept Discovery for Interpretable Few-Shot Text Classification
3. ICLR 2026Adaptive gradient descent on Riemannian manifolds and its applications to Gaussian variational inference
4. ICLR 2026Barriers for Learning in an Evolving World: Mathematical Understanding of Loss of Plasticity
5. ICLR 2026Buckingham $\pi$-Invariant Test‑Time Projection for Robust PDE Surrogate Modeling
6. ICLR 2026CFO: Learning Continuous-Time PDE Dynamics via Flow-Matched Neural Operators
7. ICLR 2026CoLA: Co-Calibrated Logit Adjustment for Long-Tailed Semi-Supervised Learning
8. ICLR 2026Combinatorial Bandit Bayesian Optimization for Tensor Outputs
9. ICLR 2026Conformalized Survival Counterfactuals Prediction for General Right-Censored Data
10. ICLR 2026Continuum Transformers Perform In-Context Learning by Operator Gradient Descent
11. ICLR 2026Deep Learning for Subspace Regression
12. ICLR 2026Difficult Examples Hurt Unsupervised Contrastive Learning: A Theoretical Perspective
13. ICLR 2026Dual Perspectives on Non-Contrastive Self-Supervised Learning
14. ICLR 2026Efficient Estimation of Kernel Surrogate Models for Task Attribution
15. ICLR 2026Enabling arbitrary inference in spatio-temporal dynamic systems: A physics-inspired perspective
16. ICLR 2026FedOpenMatch: Towards Semi-Supervised Federated Learning in Open-Set Environments
17. ICLR 2026Fingerprinting Deep Neural Networks for Ownership Protection: An Analytical Approach
18. ICLR 2026From Cheap Geometry to Expensive Physics: Elevating Neural Operators via Latent Shape Pretraining
19. ICLR 2026Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds
20. ICLR 2026Generalized Spherical Neural Operators: Green’s Function Formulation
21. ICLR 2026Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport
22. ICLR 2026Imitation Learning as Return Distribution Matching
23. ICLR 2026Improving Feasibility via Fast Autoencoder-Based Projections
24. ICLR 2026Improving LLM-based Global Optimization with Search Space Partitioning
25. ICLR 2026In Context Semi-Supervised Learning
26. ICLR 2026Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine
27. ICLR 2026Learning Dynamics of Logits Debiasing for Long-Tailed Semi-Supervised Learning
28. ICLR 2026Mixture-of-Visual-Thoughts: Exploring Context-Adaptive Reasoning Mode Selection for General Visual Reasoning
29. ICLR 2026MULTIMODALITY AS SUPERVISION: SELF-SUPERVISED SPECIALIZATION TO THE TEST ENVIRONMENT VIA MULTIMODALITY
30. ICLR 2026Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information
31. ICLR 2026Noise Tolerance of Distributionally Robust Learning
32. ICLR 2026One protein is all you need
33. ICLR 2026Operator Learning with Domain Decomposition for Geometry Generalization in PDE Solving
34. ICLR 2026Overshoot and Shrinkage in Classifier-Free Guidance: From Theory to Practice
35. ICLR 2026Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization
36. ICLR 2026Perturbation-Induced Linearization: Constructing Unlearnable Data with Solely Linear Classifiers
37. ICLR 2026Physics-Informed Inference Time Scaling for Solving High-Dimensional Partial Differential Equations
38. ICLR 2026RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data
39. ICLR 2026Riesz Neural Operator for Solving Partial Differential Equations
40. ICLR 2026Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data
41. ICLR 2026Robustness in the Face of Partial Identifiability in Reward Learning
42. ICLR 2026SCAD: Super-Class-Aware Debiasing for Long-Tailed Semi-Supervised Learning
43. ICLR 2026Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems
44. ICLR 2026Self-Supervised Learning from Structural Invariance
45. ICLR 2026SeRI: Gradient-Free Sensitive Region Identification in Decision-Based Black-Box Attacks
46. ICLR 2026SFT Doesn’t Always Hurt General Capabilities: Revisiting Domain-Specific Fine-Tuning in LLMs
47. ICLR 2026SNAP-UQ: Self-supervised Next-Activation Prediction for Single-Pass Uncertainty in TinyML
48. ICLR 2026Towards Dynamic Interleaving Optimizers

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.