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

98 papers, page 2 of 2

51. NeurIPS 2023Label-efficient Segmentation via Affinity Propagation
52. NeurIPS 2023Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment
53. NeurIPS 2023Learning From Biased Soft Labels
54. NeurIPS 2023Learning Interpretable Low-dimensional Representation via Physical Symmetry
55. NeurIPS 2023Lo-Hi: Practical ML Drug Discovery Benchmark
56. NeurIPS 2023Low-shot Object Learning with Mutual Exclusivity Bias
57. NeurIPS 2023Machine learning detects terminal singularities
58. NeurIPS 2023Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off
59. NeurIPS 2023Masked Image Residual Learning for Scaling Deeper Vision Transformers
60. NeurIPS 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
61. NeurIPS 2023Metis: Understanding and Enhancing In-Network Regular Expressions
62. NeurIPS 2023Minimum-Risk Recalibration of Classifiers
63. NeurIPS 2023Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder
64. NeurIPS 2023Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection
65. NeurIPS 2023No Representation Rules Them All in Category Discovery
66. NeurIPS 2023On Separate Normalization in Self-supervised Transformers
67. NeurIPS 2023On the Exploitability of Instruction Tuning
68. NeurIPS 2023On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training
69. NeurIPS 2023OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
70. NeurIPS 2023Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning
71. NeurIPS 2023Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage
72. NeurIPS 2023PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
73. NeurIPS 2023Relax, it doesn’t matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
74. NeurIPS 2023Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
75. NeurIPS 2023RevColV2: Exploring Disentangled Representations in Masked Image Modeling
76. NeurIPS 2023RGMIL: Guide Your Multiple-Instance Learning Model with Regressor
77. NeurIPS 2023Robust and Actively Secure Serverless Collaborative Learning
78. NeurIPS 2023Safety Verification of Decision-Tree Policies in Continuous Time
79. NeurIPS 2023SALSA VERDE: a machine learning attack on LWE with sparse small secrets
80. NeurIPS 2023Sample based Explanations via Generalized Representers
81. NeurIPS 2023Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
82. NeurIPS 2023Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
83. NeurIPS 2023Self-Supervised Motion Magnification by Backpropagating Through Optical Flow
84. NeurIPS 2023Self-supervised Object-Centric Learning for Videos
85. NeurIPS 2023Self-Supervised Reinforcement Learning that Transfers using Random Features
86. NeurIPS 2023Self-Supervised Visual Acoustic Matching
87. NeurIPS 2023Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration
88. NeurIPS 2023Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition
89. NeurIPS 2023Switching Temporary Teachers for Semi-Supervised Semantic Segmentation
90. NeurIPS 2023Tanimoto Random Features for Scalable Molecular Machine Learning
91. NeurIPS 2023The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
92. NeurIPS 2023Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
93. NeurIPS 2023Transfer Learning with Affine Model Transformation
94. NeurIPS 2023Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data
95. NeurIPS 2023UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition
96. NeurIPS 2023Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts
97. NeurIPS 2023Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems
98. NeurIPS 2023Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets

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.