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

731 papers, page 7 of 15

301. NeurIPS 2024Boosting Transferability and Discriminability for Time Series Domain Adaptation
302. NeurIPS 2024Boundary Matters: A Bi-Level Active Finetuning Method
303. NeurIPS 2024Breaking Determinism: Fuzzy Modeling of Sequential Recommendation Using Discrete State Space Diffusion Model
304. NeurIPS 2024Breaking Semantic Artifacts for Generalized AI-generated Image Detection
305. NeurIPS 2024Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?
306. NeurIPS 2024Chain of Thoughtlessness? An Analysis of CoT in Planning
307. NeurIPS 2024Classification Done Right for Vision-Language Pre-Training
308. NeurIPS 2024CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning
309. NeurIPS 2024CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
310. NeurIPS 2024Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling
311. NeurIPS 2024Collaborative Refining for Learning from Inaccurate Labels
312. NeurIPS 2024CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training
313. NeurIPS 2024Combining Statistical Depth and Fermat Distance for Uncertainty Quantification
314. NeurIPS 2024Computerized Adaptive Testing via Collaborative Ranking
315. NeurIPS 2024Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
316. NeurIPS 2024Conditional Outcome Equivalence: A Quantile Alternative to CATE
317. NeurIPS 2024Connecting Joint-Embedding Predictive Architecture with Contrastive Self-supervised Learning
318. NeurIPS 2024Construction and Application of Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model
319. NeurIPS 2024Continuous Contrastive Learning for Long-Tailed Semi-Supervised Recognition
320. NeurIPS 2024Cross-Device Collaborative Test-Time Adaptation
321. NeurIPS 2024CryoSPIN: Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference
322. NeurIPS 2024CSPG: Crossing Sparse Proximity Graphs for Approximate Nearest Neighbor Search
323. NeurIPS 2024Customizing Language Models with Instance-wise LoRA for Sequential Recommendation
324. NeurIPS 2024CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns
325. NeurIPS 2024DALD: Improving Logits-based Detector without Logits from Black-box LLMs
326. NeurIPS 2024Data Acquisition via Experimental Design for Data Markets
327. NeurIPS 2024Data-Efficient Learning with Neural Programs
328. NeurIPS 2024Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context Learning
329. NeurIPS 2024DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting
330. NeurIPS 2024Decoupling Semantic Similarity from Spatial Alignment for Neural Networks.
331. NeurIPS 2024DECRL: A Deep Evolutionary Clustering Jointed Temporal Knowledge Graph Representation Learning Approach
332. NeurIPS 2024Deep Learning Through A Telescoping Lens: A Simple Model Provides Empirical Insights On Grokking, Gradient Boosting & Beyond
333. NeurIPS 2024Deep Submodular Peripteral Networks
334. NeurIPS 2024DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching
335. NeurIPS 2024DeiSAM: Segment Anything with Deictic Prompting
336. NeurIPS 2024DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking
337. NeurIPS 2024Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval
338. NeurIPS 2024DePLM: Denoising Protein Language Models for Property Optimization
339. NeurIPS 2024Derivative-enhanced Deep Operator Network
340. NeurIPS 2024Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization
341. NeurIPS 2024Detecting Bugs with Substantial Monetary Consequences by LLM and Rule-based Reasoning
342. NeurIPS 2024Differentially Private Graph Diffusion with Applications in Personalized PageRanks
343. NeurIPS 2024DiffLight: A Partial Rewards Conditioned Diffusion Model for Traffic Signal Control with Missing Data
344. NeurIPS 2024DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis
345. NeurIPS 2024Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis
346. NeurIPS 2024Dissect Black Box: Interpreting for Rule-Based Explanations in Unsupervised Anomaly Detection
347. NeurIPS 2024Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
348. NeurIPS 2024Diversify, Contextualize, and Adapt: Efficient Entropy Modeling for Neural Image Codec
349. NeurIPS 2024Double-Ended Synthesis Planning with Goal-Constrained Bidirectional Search
350. NeurIPS 2024DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection

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.