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 27 of 29

1301. ICML 2023Learning the Right Layers a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs
1302. ICML 2023Loss Balancing for Fair Supervised Learning
1303. ICML 2023Machine Learning Force Fields with Data Cost Aware Training
1304. ICML 2023Minimizing Trajectory Curvature of ODE-based Generative Models
1305. ICML 2023Neural Inverse Operators for Solving PDE Inverse Problems
1306. ICML 2023Neural Status Registers
1307. ICML 2023Not All Semantics are Created Equal: Contrastive Self-supervised Learning with Automatic Temperature Individualization
1308. ICML 2023NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data
1309. ICML 2023On the Stepwise Nature of Self-Supervised Learning
1310. ICML 2023Optimizing Hyperparameters with Conformal Quantile Regression
1311. ICML 2023Random Teachers are Good Teachers
1312. ICML 2023RankMe: Assessing the Downstream Performance of Pretrained Self-Supervised Representations by Their Rank
1313. ICML 2023Sample Complexity of Probability Divergences under Group Symmetry
1314. ICML 2023Selective Machine Learning of the Average Treatment Effect with an Invalid Instrumental Variable
1315. ICML 2023Self-supervised learning of Split Invariant Equivariant representations
1316. ICML 2023Semi-Supervised Offline Reinforcement Learning with Action-Free Trajectories
1317. ICML 2023Short-lived High-volume Bandits
1318. ICML 2023Spherical Fourier Neural Operators: Learning Stable Dynamics on the Sphere
1319. ICML 2023Statistical Inference and A/B Testing for First-Price Pacing Equilibria
1320. ICML 2023Towards Constituting Mathematical Structures for Learning to Optimize
1321. ICML 2023Towards Quantum Machine Learning for Constrained Combinatorial Optimization: a Quantum QAP Solver
1322. ICML 2023Training Deep Surrogate Models with Large Scale Online Learning
1323. ICML 2023Underspecification Presents Challenges for Credibility in Modern Machine Learning
1324. ICML 2023Variational Autoencoding Neural Operators
1325. ICML 2023Weakly Supervised Regression with Interval Targets
1326. ICML 2023Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise?
1327. NeurIPS 2023A General Framework for Equivariant Neural Networks on Reductive Lie Groups
1328. NeurIPS 2023A General Framework for Robust G-Invariance in G-Equivariant Networks
1329. NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
1330. NeurIPS 2023A Unified Approach to Count-Based Weakly Supervised Learning
1331. NeurIPS 2023AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
1332. NeurIPS 2023Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions
1333. NeurIPS 2023An Adaptive Algorithm for Learning with Unknown Distribution Drift
1334. NeurIPS 2023Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods
1335. NeurIPS 2023Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression
1336. NeurIPS 2023Binary Classification with Confidence Difference
1337. NeurIPS 2023Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
1338. NeurIPS 2023CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
1339. NeurIPS 2023Can semi-supervised learning use all the data effectively? A lower bound perspective
1340. NeurIPS 2023CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
1341. NeurIPS 2023Characterizing the Impacts of Semi-supervised Learning for Weak Supervision
1342. NeurIPS 2023Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
1343. NeurIPS 2023ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
1344. NeurIPS 2023Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering
1345. NeurIPS 2023Combating Representation Learning Disparity with Geometric Harmonization
1346. NeurIPS 2023Conditional independence testing under misspecified inductive biases
1347. NeurIPS 2023Covariance-adaptive best arm identification
1348. NeurIPS 2023Cross-Scale MAE: A Tale of Multiscale Exploitation in Remote Sensing
1349. NeurIPS 2023Curriculum Learning With Infant Egocentric Videos
1350. NeurIPS 2023DAW: Exploring the Better Weighting Function for Semi-supervised Semantic Segmentation

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.