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

375 papers, page 3 of 8

101. NeurIPS 2024End-to-End Ontology Learning with Large Language Models
102. NeurIPS 2024Enhancing Domain Adaptation through Prompt Gradient Alignment
103. NeurIPS 2024Enhancing LLM Reasoning via Vision-Augmented Prompting
104. NeurIPS 2024Enhancing Semi-Supervised Learning via Representative and Diverse Sample Selection
105. NeurIPS 2024Evaluate calibration of language models with folktexts
106. NeurIPS 2024Evidential Mixture Machines: Deciphering Multi-Label Correlations for Active Learning Sensitivity
107. NeurIPS 2024Evidential Stochastic Differential Equations for Time-Aware Sequential Recommendation
108. NeurIPS 2024Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems
109. NeurIPS 2024Expert-level protocol translation for self-driving labs
110. NeurIPS 2024Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion
111. NeurIPS 2024Exploiting Representation Curvature for Boundary Detection in Time Series
112. NeurIPS 2024Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation
113. NeurIPS 2024Extending Multi-modal Contrastive Representations
114. NeurIPS 2024Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations
115. NeurIPS 2024Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization
116. NeurIPS 2024Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
117. NeurIPS 2024Federated Fine-tuning of Large Language Models under Heterogeneous Tasks and Client Resources
118. NeurIPS 2024Federated Learning over Connected Modes
119. NeurIPS 2024FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation
120. NeurIPS 2024FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction
121. NeurIPS 2024FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Making
122. NeurIPS 2024Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination
123. NeurIPS 2024Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients
124. NeurIPS 2024Fixed points of nonnegative neural networks
125. NeurIPS 2024FlexPlanner: Flexible 3D Floorplanning via Deep Reinforcement Learning in Hybrid Action Space with Multi-Modality Representation
126. NeurIPS 2024FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling
127. NeurIPS 2024Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
128. NeurIPS 2024Free-Rider and Conflict Aware Collaboration Formation for Cross-Silo Federated Learning
129. NeurIPS 2024Frequency-aware Generative Models for Multivariate Time Series Imputation
130. NeurIPS 2024From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection
131. NeurIPS 2024Full-Atom Peptide Design with Geometric Latent Diffusion
132. NeurIPS 2024Fundamental Limits of Prompt Compression: A Rate-Distortion Framework for Black-Box Language Models
133. NeurIPS 2024FUSE: Fast Unified Simulation and Estimation for PDEs
134. NeurIPS 2024FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion
135. NeurIPS 2024G3: An Effective and Adaptive Framework for Worldwide Geolocalization Using Large Multi-Modality Models
136. NeurIPS 2024Gated Inference Network: Inference and Learning State-Space Models
137. NeurIPS 2024Generalized Protein Pocket Generation with Prior-Informed Flow Matching
138. NeurIPS 2024Generative Adversarial Model-Based Optimization via Source Critic Regularization
139. NeurIPS 2024Generative Modeling of Molecular Dynamics Trajectories
140. NeurIPS 2024Genetic-guided GFlowNets for Sample Efficient Molecular Optimization
141. NeurIPS 2024Geometric Analysis of Nonlinear Manifold Clustering
142. NeurIPS 2024Get Rid of Isolation: A Continuous Multi-task Spatio-Temporal Learning Framework
143. NeurIPS 2024GFlowNet Assisted Biological Sequence Editing
144. NeurIPS 2024GITA: Graph to Visual and Textual Integration for Vision-Language Graph Reasoning
145. NeurIPS 2024Gliding over the Pareto Front with Uniform Designs
146. NeurIPS 2024Global Lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers
147. NeurIPS 2024Graph Neural Flows for Unveiling Systemic Interactions Among Irregularly Sampled Time Series
148. NeurIPS 2024Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning
149. NeurIPS 2024Hierarchical Federated Learning with Multi-Timescale Gradient Correction
150. NeurIPS 2024Hierarchical Selective Classification

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.