通用机器学习 · generalization论文趋势 2023–2026

主要结论

• 通用机器学习 · generalization论文从 2023 年的 136 篇增长到 2026 年的 152 篇，三年间扩大到约 1.1 倍。
• NeurIPS 是发通用机器学习 · generalization论文最多的会议，2023–2026 年共 207 篇，占四个会议总量的 35%。
• 交叉方向里涨得最快的是理论 · learning theory：同时属于两个主题的论文从 2023 年的 3 篇增至 2026 年的 20 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 5；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · generalization是 1.1 倍。

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 2026Asymmetric Generalization in Deep CTR Models: A Block-wise Diagnosis
• ICML 2026Anti-causal domain generalization: Leveraging unlabeled data
• ICLR 2026Generalization Below the Edge of Stability: The Role of Data Geometry
• CVPR 2026PriVi Towards a General-Purpose Video Model for Primate Behavior in
• NeurIPS 2025Automatic Visual Instrumental Variable Learning for Confounding-Resistant Domain Generalization
• ICML 2025Causality Inspired Federated Learning for OOD Generalization
• ICLR 2025Federated Domain Generalization with Data-free On-server Matching Gradient
• CVPR 2025Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain Generalization
• NeurIPS 2024Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
• ICML 2024Algorithmic Stability Unleashed: Generalization Bounds with Unbounded Losses
• ICLR 2024Adaptive Sharpness-Aware Pruning for Robust Sparse Networks
• CVPR 2024Disentangled Prompt Representation for Domain Generalization
• NeurIPS 2023A unified framework for information-theoretic generalization bounds
• ICML 2023Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
• ICLR 2023ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations
• CVPR 2023AltFreezing for More General Video Face Forgery Detection
• NeurIPS 2026Beyond Average Flatness: Domain-wise Flatness for Domain Generalization
• ICML 2026Are Object-Centric Representations Better at Compositional Generalization?
• ICLR 2026Temporal Generalization: A Reality Check
• CVPR 2026The Golden Subspace Where Efficiency Meets Generalization in Continual Test-Time

全部通用机器学习 · generalization论文

共 592 篇，第 11 / 12 页

501. ICLR 2023Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
502. ICLR 2023Leveraging Unlabeled Data to Track Memorization
503. ICLR 2023Linear Connectivity Reveals Generalization Strategies
504. ICLR 2023Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent
505. ICLR 2023Max-Margin Works while Large Margin Fails: Generalization without Uniform Convergence
506. ICLR 2023Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
507. ICLR 2023No Reason for No Supervision: Improved Generalization in Supervised Models
508. ICLR 2023On The Specialization of Neural Modules
509. ICLR 2023Over-Training with Mixup May Hurt Generalization
510. ICLR 2023PGrad: Learning Principal Gradients For Domain Generalization
511. ICLR 2023Sharper Bounds for Uniformly Stable Algorithms with Stationary Mixing Process
512. ICLR 2023SIMPLE: Specialized Model-Sample Matching for Domain Generalization
513. ICLR 2023Sub-Task Decomposition Enables Learning in Sequence to Sequence Tasks
514. ICLR 2023Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks
515. ICLR 2023Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning
516. ICLR 2023Towards the Generalization of Contrastive Self-Supervised Learning
517. ICLR 2023Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
518. ICML 2023A General Representation Learning Framework with Generalization Performance Guarantees
519. ICML 2023A Generalization of ViT/MLP-Mixer to Graphs
520. ICML 2023Abstract-to-Executable Trajectory Translation for One-Shot Task Generalization
521. ICML 2023Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions
522. ICML 2023Can Neural Network Memorization Be Localized?
523. ICML 2023Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution
524. ICML 2023Differentiable Tree Operations Promote Compositional Generalization
525. ICML 2023Distribution Free Domain Generalization
526. ICML 2023General Sequential Episodic Memory Model
527. ICML 2023Generalization Analysis for Contrastive Representation Learning
528. ICML 2023Generalization Bounds using Data-Dependent Fractal Dimensions
529. ICML 2023How much does Initialization Affect Generalization?
530. ICML 2023Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds through Algorithmic Stability
531. ICML 2023Learning to Boost Training by Periodic Nowcasting Near Future Weights
532. ICML 2023MAGANet: Achieving Combinatorial Generalization by Modeling a Group Action
533. ICML 2023Model-agnostic Measure of Generalization Difficulty
534. ICML 2023Moderately Distributional Exploration for Domain Generalization
535. ICML 2023Monotonic Location Attention for Length Generalization
536. ICML 2023On the Complexity of Bayesian Generalization
537. ICML 2023On the Generalization of Multi-modal Contrastive Learning
538. ICML 2023Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships
539. ICML 2023PAC Generalization via Invariant Representations
540. ICML 2023Robust Subtask Learning for Compositional Generalization
541. ICML 2023Test-Time Style Shifting: Handling Arbitrary Styles in Domain Generalization
542. ICML 2023The Benefits of Model-Based Generalization in Reinforcement Learning
543. ICML 2023Theory on Forgetting and Generalization of Continual Learning
544. ICML 2023Tighter Information-Theoretic Generalization Bounds from Supersamples
545. ICML 2023Toward Large Kernel Models
546. ICML 2023Towards Understanding Generalization of Graph Neural Networks
547. ICML 2023Towards Understanding Generalization of Macro-AUC in Multi-label Learning
548. ICML 2023Transformers as Algorithms: Generalization and Stability in In-context Learning
549. ICML 2023Wasserstein Barycenter Matching for Graph Size Generalization of Message Passing Neural Networks
550. ICML 2023What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · generalization论文？

共 592 篇，按年份分别是 2023 年 136 篇、2024 年 135 篇、2025 年 169 篇、2026 年 152 篇。

NeurIPS 2026 有多少篇通用机器学习 · generalization论文？

NeurIPS 2026 有 58 篇通用机器学习 · generalization论文，上一届是 61 篇。

ICLR 2026 有多少篇通用机器学习 · generalization论文？

ICLR 2026 有 38 篇通用机器学习 · generalization论文，上一届是 33 篇。

ICML 2026 有多少篇通用机器学习 · generalization论文？

ICML 2026 有 47 篇通用机器学习 · generalization论文，上一届是 61 篇。

CVPR 2026 有多少篇通用机器学习 · generalization论文？

CVPR 2026 有 9 篇通用机器学习 · generalization论文，上一届是 14 篇。

哪个会议的通用机器学习 · generalization论文最多？

NeurIPS，2023–2026 年共 207 篇。