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

372 papers, page 2 of 8

51. ICLR 2025Bayesian Optimization via Continual Variational Last Layer Training
52. ICLR 2025Boosting Ray Search Procedure of Hard-label Attacks with Transfer-based Priors
53. ICLR 2025Conditional Testing based on Localized Conformal $p$-values
54. ICLR 2025Conformalized Survival Analysis for General Right-Censored Data
55. ICLR 2025CONGO: Compressive Online Gradient Optimization
56. ICLR 2025CViT: Continuous Vision Transformer for Operator Learning
57. ICLR 2025Deconstructing Denoising Diffusion Models for Self-Supervised Learning
58. ICLR 2025Discretization-invariance? On the Discretization Mismatch Errors in Neural Operators
59. ICLR 2025Generalizable Motion Planning via Operator Learning
60. ICLR 2025Group Downsampling with Equivariant Anti-aliasing
61. ICLR 2025High-dimensional Analysis of Knowledge Distillation: Weak-to-Strong Generalization and Scaling Laws
62. ICLR 2025High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders
63. ICLR 2025Interaction Asymmetry: A General Principle for Learning Composable Abstractions
64. ICLR 2025LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
65. ICLR 2025Learning Chaos In A Linear Way
66. ICLR 2025Learning Distributions of Complex Fluid Simulations with Diffusion Graph Networks
67. ICLR 2025Lipschitz Bandits in Optimal Space
68. ICLR 2025MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
69. ICLR 2025MGCFNN: A Neural MultiGrid Solver with Novel Fourier Neural Network for High Wave Number Helmholtz Equations
70. ICLR 2025Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout
71. ICLR 2025Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning
72. ICLR 2025Noise Separation guided Candidate Label Reconstruction for Noisy Partial Label Learning
73. ICLR 2025Offline Model-Based Optimization by Learning to Rank
74. ICLR 2025Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics
75. ICLR 2025PABBO: Preferential Amortized Black-Box Optimization
76. ICLR 2025PIED: Physics-Informed Experimental Design for Inverse Problems
77. ICLR 2025PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows
78. ICLR 2025Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model
79. ICLR 2025RESuM: A Rare Event Surrogate Model for Physics Detector Design
80. ICLR 2025Self-supervised contrastive learning performs non-linear system identification
81. ICLR 2025Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent Flows
82. ICLR 2025SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning
83. ICLR 2025SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems
84. ICLR 2025T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
85. ICLR 2025Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression
86. ICLR 2025Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning
87. ICLR 2025Wasserstein-Regularized Conformal Prediction under General Distribution Shift
88. ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
89. ICML 2025Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
90. ICML 2025Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
91. ICML 2025Active Learning with Selective Time-Step Acquisition for PDEs
92. ICML 2025Adaptive Partitioning Schemes for Optimistic Optimization
93. ICML 2025Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
94. ICML 2025An Analysis of Quantile Temporal-Difference Learning
95. ICML 2025Approximately Correct Label Distribution Learning
96. ICML 2025Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
97. ICML 2025Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
98. ICML 2025Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
99. ICML 2025BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
100. ICML 2025Calibrated Physics-Informed Uncertainty Quantification

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.