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

1,424 papers, page 2 of 29

51. ICLR 2026Generalised Flow Maps for Few-Step Generative Modelling on Riemannian Manifolds
52. ICLR 2026Generalized Spherical Neural Operators: Green’s Function Formulation
53. ICLR 2026Hyperparameter Trajectory Inference with Conditional Lagrangian Optimal Transport
54. ICLR 2026Imitation Learning as Return Distribution Matching
55. ICLR 2026Improving Feasibility via Fast Autoencoder-Based Projections
56. ICLR 2026Improving LLM-based Global Optimization with Search Space Partitioning
57. ICLR 2026In Context Semi-Supervised Learning
58. ICLR 2026Knowledgeable Language Models as Black-Box Optimizers for Personalized Medicine
59. ICLR 2026Learning Dynamics of Logits Debiasing for Long-Tailed Semi-Supervised Learning
60. ICLR 2026Mixture-of-Visual-Thoughts: Exploring Context-Adaptive Reasoning Mode Selection for General Visual Reasoning
61. ICLR 2026MULTIMODALITY AS SUPERVISION: SELF-SUPERVISED SPECIALIZATION TO THE TEST ENVIRONMENT VIA MULTIMODALITY
62. ICLR 2026Nearly-Optimal Bandit Learning in Stackelberg Games with Side Information
63. ICLR 2026Noise Tolerance of Distributionally Robust Learning
64. ICLR 2026One protein is all you need
65. ICLR 2026Operator Learning with Domain Decomposition for Geometry Generalization in PDE Solving
66. ICLR 2026Overshoot and Shrinkage in Classifier-Free Guidance: From Theory to Practice
67. ICLR 2026Pareto-Conditioned Diffusion Models for Offline Multi-Objective Optimization
68. ICLR 2026Perturbation-Induced Linearization: Constructing Unlearnable Data with Solely Linear Classifiers
69. ICLR 2026Physics-Informed Inference Time Scaling for Solving High-Dimensional Partial Differential Equations
70. ICLR 2026RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data
71. ICLR 2026Riesz Neural Operator for Solving Partial Differential Equations
72. ICLR 2026Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data
73. ICLR 2026Robustness in the Face of Partial Identifiability in Reward Learning
74. ICLR 2026SCAD: Super-Class-Aware Debiasing for Long-Tailed Semi-Supervised Learning
75. ICLR 2026Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems
76. ICLR 2026Self-Supervised Learning from Structural Invariance
77. ICLR 2026SeRI: Gradient-Free Sensitive Region Identification in Decision-Based Black-Box Attacks
78. ICLR 2026SFT Doesn’t Always Hurt General Capabilities: Revisiting Domain-Specific Fine-Tuning in LLMs
79. ICLR 2026SNAP-UQ: Self-supervised Next-Activation Prediction for Single-Pass Uncertainty in TinyML
80. ICLR 2026Towards Dynamic Interleaving Optimizers
81. ICML 2026$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
82. ICML 2026A Minimax Approach for Optimal Intervention Policy Learning with Two-Stage Outcomes
83. ICML 2026Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
84. ICML 2026Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems
85. ICML 2026Advancing Analytic Class-Incremental Learning through Vision-Language Calibration
86. ICML 2026Adversarial Robustness of Implicit Neural Representation-Based Classifiers
87. ICML 2026AES: Curing Optimizer Blindness in Long-Tailed Recognition via State-Aware Correction
88. ICML 2026Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
89. ICML 2026Approximation Preserving Coresets
90. ICML 2026Beyond Accuracy and Complexity: The Effective Information Criterion for Structurally Stable Symbolic Regression
91. ICML 2026Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-Supervised Learning
92. ICML 2026Beyond Magnitude: Scale-Invariant Evidential Fusion for Multi-View Classification
93. ICML 2026Bio-Inspired Self-Supervised Learning for Wrist-worn Accelerometer Data
94. ICML 2026BTSP-CAM: A Brain-Inspired Geometric Memory for Class-Incremental Learning
95. ICML 2026Can local learning match self-supervised backpropagation?
96. ICML 2026Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
97. ICML 2026CINOC: Cardinality-Invariant Neural Operator Policies for Scalable PDE Control
98. ICML 2026Class-Prior Perturbation-Robust Regularization for Imbalanced Unreliable Partial Label Learning
99. ICML 2026CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
100. ICML 2026CoEvol-NO: State and Coordinate Co-Evolution with an Error-Driven Predictor-Corrector Paradigm for Neural Operator Transformer

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.