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

45 papers, page 1 of 1

1. ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
2. ICLR 2023A theoretical study of inductive biases in contrastive learning
3. ICLR 2023Agnostic Learning of General ReLU Activation Using Gradient Descent
4. ICLR 2023Coupled Multiwavelet Operator Learning for Coupled Differential Equations
5. ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
6. ICLR 2023Don’t fear the unlabelled: safe semi-supervised learning via debiasing
7. ICLR 2023EA-HAS-Bench: Energy-aware Hyperparameter and Architecture Search Benchmark
8. ICLR 2023Effective Self-supervised Pre-training on Low-compute Networks without Distillation
9. ICLR 2023Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems
10. ICLR 2023Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders
11. ICLR 2023FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
12. ICLR 2023Guiding continuous operator learning through Physics-based boundary constraints
13. ICLR 2023How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study
14. ICLR 2023HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork
15. ICLR 2023Identifiability Results for Multimodal Contrastive Learning
16. ICLR 2023Imbalanced Semi-supervised Learning with Bias Adaptive Classifier
17. ICLR 2023InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
18. ICLR 2023Label Propagation with Weak Supervision
19. ICLR 2023Learning Controllable Adaptive Simulation for Multi-resolution Physics
20. ICLR 2023Minimax Optimal Kernel Operator Learning via Multilevel Training
21. ICLR 2023MocoSFL: enabling cross-client collaborative self-supervised learning
22. ICLR 2023No Reason for No Supervision: Improved Generalization in Supervised Models
23. ICLR 2023Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities
24. ICLR 2023On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.
25. ICLR 2023One Transformer Can Understand Both 2D & 3D Molecular Data
26. ICLR 2023Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training
27. ICLR 2023Progressively Compressed Auto-Encoder for Self-supervised Representation Learning
28. ICLR 2023RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
29. ICLR 2023Sampling-based inference for large linear models, with application to linearised Laplace
30. ICLR 2023Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
31. ICLR 2023Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance
32. ICLR 2023Self-supervised learning with rotation-invariant kernels
33. ICLR 2023Semi-supervised learning with a principled likelihood from a generative model of data curation
34. ICLR 2023SimPer: Simple Self-Supervised Learning of Periodic Targets
35. ICLR 2023SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning
36. ICLR 2023Spectral Augmentation for Self-Supervised Learning on Graphs
37. ICLR 2023Symmetric Pruning in Quantum Neural Networks
38. ICLR 2023Temperature Schedules for self-supervised contrastive methods on long-tail data
39. ICLR 2023The hidden uniform cluster prior in self-supervised learning
40. ICLR 2023Towards the Generalization of Contrastive Self-Supervised Learning
41. ICLR 2023Transformer Meets Boundary Value Inverse Problems
42. ICLR 2023Unbiased Supervised Contrastive Learning
43. ICLR 2023Understanding The Robustness of Self-supervised Learning Through Topic Modeling
44. ICLR 2023Weighted Ensemble Self-Supervised Learning
45. ICLR 2023What shapes the loss landscape of self supervised learning?

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.