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 16 of 29

751. ICML 2024Bootstrap AutoEncoders With Contrastive Paradigm for Self-supervised Gaze Estimation
752. ICML 2024Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach
753. ICML 2024Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
754. ICML 2024ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
755. ICML 2024Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning
756. ICML 2024Counterfactual Metarules for Local and Global Recourse
757. ICML 2024Deep Stochastic Mechanics
758. ICML 2024Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
759. ICML 2024Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
760. ICML 2024Equivariant Graph Neural Operator for Modeling 3D Dynamics
761. ICML 2024Exploring Correlations of Self-Supervised Tasks for Graphs
762. ICML 2024FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data
763. ICML 2024From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble
764. ICML 2024Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution
765. ICML 2024High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
766. ICML 2024Implicit Representations via Operator Learning
767. ICML 2024Improved Operator Learning by Orthogonal Attention
768. ICML 2024In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
769. ICML 2024Information Flow in Self-Supervised Learning
770. ICML 2024Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
771. ICML 2024MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
772. ICML 2024Neural Operators with Localized Integral and Differential Kernels
773. ICML 2024OTMatch: Improving Semi-Supervised Learning with Optimal Transport
774. ICML 2024OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
775. ICML 2024Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
776. ICML 2024Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
777. ICML 2024Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation
778. ICML 2024Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation
779. ICML 2024Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
780. ICML 2024SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification
781. ICML 2024Towards Realistic Model Selection for Semi-supervised Learning
782. ICML 2024Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation
783. ICML 2024Unveiling the Dynamics of Information Interplay in Supervised Learning
784. ICML 2024UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
785. ICML 2024Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
786. ICML 2024Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
787. NeurIPS 2024(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
788. NeurIPS 20243D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization
789. NeurIPS 2024A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness
790. NeurIPS 2024A Structure-Aware Framework for Learning Device Placements on Computation Graphs
791. NeurIPS 2024A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm
792. NeurIPS 2024A theoretical design of concept sets: improving the predictability of concept bottleneck models
793. NeurIPS 2024A Theoretical Perspective for Speculative Decoding Algorithm
794. NeurIPS 2024Accurate and Steady Inertial Pose Estimation through Sequence Structure Learning and Modulation
795. NeurIPS 2024Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
796. NeurIPS 2024Active Learning with LLMs for Partially Observed and Cost-Aware Scenarios
797. NeurIPS 2024Active preference learning for ordering items in- and out-of-sample
798. NeurIPS 2024Active Set Ordering
799. NeurIPS 2024Active, anytime-valid risk controlling prediction sets
800. NeurIPS 2024Ad Auctions for LLMs via Retrieval Augmented Generation

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.