通用机器学习 · supervised learning论文趋势 2023–2026
通用机器学习：supervised_learning
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 1,425 篇被归入该主题的论文。
主要结论
- 通用机器学习 · supervised learning论文从 2023 年的 263 篇增长到 2026 年的 279 篇，三年间扩大到约 1.1 倍。
- NeurIPS 是发通用机器学习 · supervised learning论文最多的会议，2023–2026 年共 731 篇，占四个会议总量的 51%。
- 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 9 篇。
- 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 3；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · supervised learning是 1.1 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 98 | 45 | 44 | 76 | 263 |
| 2024 | 375 | 41 | 44 | 51 | 511 |
| 2025 | 171 | 40 | 114 | 47 | 372 |
| 2026 | 87 | 48 | 111 | 33 | 279 |
代表论文
按年份和会议均匀挑选，方便快速看到每一届的样貌
- 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
全部通用机器学习 · supervised learning论文
共 731 篇，第 6 / 15 页
- NeurIPS 2025UniMRSeg: Unified Modality-Relax Segmentation via Hierarchical Self-Supervised Compensation
- NeurIPS 2025Variational Supervised Contrastive Learning
- NeurIPS 2025Vertical Federated Feature Screening
- NeurIPS 2025ViSPLA: Visual Iterative Self-Prompting for Language-Guided 3D Affordance Learning
- NeurIPS 2025What Do Latent Action Models Actually Learn?
- NeurIPS 2025What Does It Take to Build a Performant Selective Classifier?
- NeurIPS 2025When No Paths Lead to Rome: Benchmarking Systematic Neural Relational Reasoning
- NeurIPS 2025WolBanking77: Wolof Banking Speech Intent Classification Dataset
- NeurIPS 2024(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
- NeurIPS 20243D Structure Prediction of Atomic Systems with Flow-based Direct Preference Optimization
- NeurIPS 2024A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness
- NeurIPS 2024A Structure-Aware Framework for Learning Device Placements on Computation Graphs
- NeurIPS 2024A Swiss Army Knife for Heterogeneous Federated Learning: Flexible Coupling via Trace Norm
- NeurIPS 2024A theoretical design of concept sets: improving the predictability of concept bottleneck models
- NeurIPS 2024A Theoretical Perspective for Speculative Decoding Algorithm
- NeurIPS 2024Accurate and Steady Inertial Pose Estimation through Sequence Structure Learning and Modulation
- NeurIPS 2024Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes
- NeurIPS 2024Active Learning with LLMs for Partially Observed and Cost-Aware Scenarios
- NeurIPS 2024Active preference learning for ordering items in- and out-of-sample
- NeurIPS 2024Active Set Ordering
- NeurIPS 2024Active, anytime-valid risk controlling prediction sets
- NeurIPS 2024Ad Auctions for LLMs via Retrieval Augmented Generation
- NeurIPS 2024AdaNovo: Towards Robust \emph{De Novo} Peptide Sequencing in Proteomics against Data Biases
- NeurIPS 2024Adaptive Domain Learning for Cross-domain Image Denoising
- NeurIPS 2024Addressing Hidden Confounding with Heterogeneous Observational Datasets for Recommendation
- NeurIPS 2024Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
- NeurIPS 2024Amortized Active Causal Induction with Deep Reinforcement Learning
- NeurIPS 2024Amortized Planning with Large-Scale Transformers: A Case Study on Chess
- NeurIPS 2024An Autoencoder-Like Nonnegative Matrix Co-Factorization for Improved Student Cognitive Modeling
- NeurIPS 2024An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem
- NeurIPS 2024Antigen-Specific Antibody Design via Direct Energy-based Preference Optimization
- NeurIPS 2024Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport Loss
- NeurIPS 2024Approximating mutual information of high-dimensional variables using learned representations
- NeurIPS 2024Are Large-scale Soft Labels Necessary for Large-scale Dataset Distillation?
- NeurIPS 2024Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective
- NeurIPS 2024AUC Maximization under Positive Distribution Shift
- NeurIPS 2024Autoformalize Mathematical Statements by Symbolic Equivalence and Semantic Consistency
- NeurIPS 2024AutoManual: Constructing Instruction Manuals by LLM Agents via Interactive Environmental Learning
- NeurIPS 2024Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records
- NeurIPS 2024Automatic Outlier Rectification via Optimal Transport
- NeurIPS 2024Automatically Learning Hybrid Digital Twins of Dynamical Systems
- NeurIPS 2024BackTime: Backdoor Attacks on Multivariate Time Series Forecasting
- NeurIPS 2024Batched Energy-Entropy acquisition for Bayesian Optimization
- NeurIPS 2024Bayesian Adaptive Calibration and Optimal Design
- NeurIPS 2024Bayesian Optimisation with Unknown Hyperparameters: Regret Bounds Logarithmically Closer to Optimal
- NeurIPS 2024Better by default: Strong pre-tuned MLPs and boosted trees on tabular data
- NeurIPS 2024Beyond Efficiency: Molecular Data Pruning for Enhanced Generalization
- NeurIPS 2024BiScope: AI-generated Text Detection by Checking Memorization of Preceding Tokens
- NeurIPS 2024Boosted Conformal Prediction Intervals
- NeurIPS 2024Boosting the Transferability of Adversarial Attack on Vision Transformer with Adaptive Token Tuning
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后，写综述、挑方向或准备投稿时，不用离开对话框就能拿到这页的数字：每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文，AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查通用机器学习 · supervised learning在 NeurIPS 2023–2026 的论文趋势，哪一年涨得最快？
AI 会调用的工具：get_topic_stats {"topic": "gml-supervised-learning"}
常见问题
- 2023–2026 年四大会议一共有多少篇通用机器学习 · supervised learning论文？
- 共 1,425 篇，按年份分别是 2023 年 263 篇、2024 年 511 篇、2025 年 372 篇、2026 年 279 篇。
- NeurIPS 2026 有多少篇通用机器学习 · supervised learning论文？
- NeurIPS 2026 有 87 篇通用机器学习 · supervised learning论文，上一届是 171 篇。
- ICLR 2026 有多少篇通用机器学习 · supervised learning论文？
- ICLR 2026 有 48 篇通用机器学习 · supervised learning论文，上一届是 40 篇。
- ICML 2026 有多少篇通用机器学习 · supervised learning论文？
- ICML 2026 有 111 篇通用机器学习 · supervised learning论文，上一届是 114 篇。
- CVPR 2026 有多少篇通用机器学习 · supervised learning论文？
- CVPR 2026 有 33 篇通用机器学习 · supervised learning论文，上一届是 47 篇。
- 哪个会议的通用机器学习 · supervised learning论文最多？
- NeurIPS，2023–2026 年共 731 篇。