{"total":110,"rows":[{"id":"2106.02073","title":"Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path","created":"2021-06-03","cited_by_count":158,"area":null},{"id":"2106.09647","title":"Deep Learning Through the Lens of Example Difficulty","created":"2021-06-17","cited_by_count":141,"area":null},{"id":"2106.13799","title":"Assessing Generalization of SGD via Disagreement","created":"2021-06-25","cited_by_count":117,"area":null},{"id":"2107.03315","title":"Predicting with Confidence on Unseen Distributions","created":"2021-07-07","cited_by_count":116,"area":null},{"id":"2110.02095","title":"Exploring the Limits of Large Scale Pre-training","created":"2021-10-05","cited_by_count":104,"area":null},{"id":"2206.04041","title":"Neural Collapse: A Review on Modelling Principles and Generalization","created":"2022-06-08","cited_by_count":95,"area":null},{"id":"2302.14040","title":"Permutation Equivariant Neural Functionals","created":"2023-02-27","cited_by_count":70,"area":null},{"id":"2106.05961","title":"What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?","created":"2021-06-10","cited_by_count":63,"area":null},{"id":"2305.13546","title":"Neural Functional Transformers","created":"2023-05-22","cited_by_count":52,"area":null},{"id":"2406.09997","title":"Towards Scalable and Versatile Weight Space Learning","created":"2024-06-14","cited_by_count":41,"area":null},{"id":"2111.06977","title":"Scalable Diverse Model Selection for Accessible Transfer Learning","created":"2021-11-12","cited_by_count":40,"area":null},{"id":"2209.13083","title":"Why neural networks find simple solutions: the many regularizers of geometric complexity","created":"2022-09-27","cited_by_count":39,"area":null},{"id":"2209.14764","title":"Model Zoos: A Dataset of Diverse Populations of Neural Network Models","created":"2022-09-29","cited_by_count":39,"area":null},{"id":"2104.05641","title":"Generalization bounds via distillation","created":"2021-04-12","cited_by_count":34,"area":null},{"id":"2104.05097","title":"Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networks","created":"2021-04-11","cited_by_count":30,"area":null},{"id":"2110.02180","title":"Noisy Feature Mixup","created":"2021-10-05","cited_by_count":27,"area":null},{"id":"2106.03314","title":"Measuring Generalization with Optimal Transport","created":"2021-06-07","cited_by_count":25,"area":null},{"id":"2207.07065","title":"On the Strong Correlation Between Model Invariance and Generalization","created":"2022-07-14","cited_by_count":23,"area":null},{"id":"2302.01094","title":"Confidence and Dispersity Speak: Characterising Prediction Matrix for Unsupervised Accuracy Estimation","created":"2023-02-02","cited_by_count":22,"area":null},{"id":"2210.05129","title":"Multi-Object Navigation with dynamically learned neural implicit representations","created":"2022-10-11","cited_by_count":21,"area":null},{"id":"2502.07551","title":"Early Stopping Against Label Noise Without Validation Data","created":"2025-02-11","cited_by_count":21,"area":null},{"id":"2202.02842","title":"Evaluating natural language processing models with generalization metrics that do not need access to any training or testing data","created":"2022-02-06","cited_by_count":19,"area":null},{"id":"2305.16427","title":"Neural (Tangent Kernel) Collapse","created":"2023-05-25","cited_by_count":18,"area":null},{"id":"2306.16180","title":"Pseudo-Bag Mixup Augmentation for Multiple Instance Learning-Based Whole Slide Image Classification","created":"2023-06-28","cited_by_count":18,"area":null},{"id":"2401.12689","title":"Energy-based Automated Model Evaluation","created":"2024-01-23","cited_by_count":17,"area":null},{"id":"2303.15488","title":"On the Importance of Feature Separability in Predicting Out-Of-Distribution Error","created":"2023-03-27","cited_by_count":15,"area":null},{"id":"2106.04765","title":"Predicting Deep Neural Network Generalization with Perturbation Response Curves","created":"2021-06-09","cited_by_count":14,"area":null},{"id":"2212.06925","title":"On the Relationship Between Explanation and Prediction: A Causal View","created":"2022-12-13","cited_by_count":14,"area":null},{"id":"2504.05461","title":"Intermediate Layer Classifiers for OOD generalization","created":"2025-04-07","cited_by_count":14,"area":null},{"id":"2101.06459","title":"Robustness to Augmentations as a Generalization metric","created":"2021-01-16","cited_by_count":13,"area":null},{"id":"2103.06219","title":"Why flatness does and does not correlate with generalization for deep neural networks","created":"2021-03-10","cited_by_count":13,"area":null},{"id":"2211.01258","title":"Instance-Dependent Generalization Bounds via Optimal Transport","created":"2022-11-02","cited_by_count":13,"area":null},{"id":"2204.08624","title":"Topology and geometry of data manifold in deep learning","created":"2022-04-19","cited_by_count":12,"area":null},{"id":"2401.01867","title":"Dataset Difficulty and the Role of Inductive Bias","created":"2024-01-03","cited_by_count":12,"area":null},{"id":"2101.09849","title":"Deep Learning Generalization and the Convex Hull of Training Sets","created":"2021-01-25","cited_by_count":10,"area":null},{"id":"2103.06002","title":"Robustness to Pruning Predicts Generalization in Deep Neural Networks","created":"2021-03-10","cited_by_count":10,"area":null},{"id":"2112.00694","title":"Label-Free Model Evaluation with Semi-Structured Dataset Representations","created":"2021-12-01","cited_by_count":10,"area":null},{"id":"2206.01986","title":"Delving into the Openness of CLIP","created":"2022-06-04","cited_by_count":10,"area":null},{"id":"2308.09037","title":"MarginMatch: Improving Semi-Supervised Learning with Pseudo-Margins","created":"2023-08-17","cited_by_count":10,"area":null},{"id":"2110.15288","title":"Hyper-Representations: Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction","created":"2021-10-28","cited_by_count":9,"area":null},{"id":"2203.12330","title":"Predicting the generalization gap in neural networks using topological data analysis","created":"2022-03-23","cited_by_count":9,"area":null},{"id":"2108.10310","title":"Ranking Models in Unlabeled New Environments","created":"2021-08-23","cited_by_count":8,"area":null},{"id":"2110.06537","title":"Well-classified Examples are Underestimated in Classification with Deep Neural Networks","created":"2021-10-13","cited_by_count":8,"area":null},{"id":"2209.10080","title":"Deep Double Descent via Smooth Interpolation","created":"2022-09-21","cited_by_count":8,"area":null},{"id":"2401.03350","title":"Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks","created":"2024-01-07","cited_by_count":8,"area":null},{"id":"2103.13598","title":"Recent Advances in Large Margin Learning","created":"2021-03-25","cited_by_count":7,"area":null},{"id":"2309.09403","title":"Selecting which Dense Retriever to use for Zero-Shot Search","created":"2023-09-18","cited_by_count":7,"area":null},{"id":"2402.13285","title":"Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures","created":"2024-02-19","cited_by_count":7,"area":null},{"id":"2411.06919","title":"Understanding Generalization in Quantum Machine Learning with Margins","created":"2024-11-11","cited_by_count":7,"area":null},{"id":"2111.14212","title":"On Predicting Generalization using GANs","created":"2021-11-28","cited_by_count":6,"area":null},{"id":"2308.11111","title":"CAME: Contrastive Automated Model Evaluation","created":"2023-08-22","cited_by_count":6,"area":null},{"id":"2403.13803","title":"Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments","created":"2024-03-20","cited_by_count":6,"area":null},{"id":"2205.00953","title":"BERTops: Studying BERT Representations under a Topological Lens","created":"2022-05-02","cited_by_count":5,"area":null},{"id":"2205.03940","title":"Investigating Generalization by Controlling Normalized Margin","created":"2022-05-08","cited_by_count":5,"area":null},{"id":"2306.03406","title":"Deep neural networks architectures from the perspective of manifold learning","created":"2023-06-06","cited_by_count":5,"area":null},{"id":"2406.18630","title":"Improving Hyperparameter Optimization with Checkpointed Model Weights","created":"2024-06-26","cited_by_count":5,"area":null},{"id":"2501.12597","title":"Multi-Instance Partial-Label Learning with Margin Adjustment","created":"2025-01-22","cited_by_count":5,"area":null},{"id":"2106.00012","title":"Persistent Homology Captures the Generalization of Neural Networks Without A Validation Set","created":"2021-05-31","cited_by_count":4,"area":null},{"id":"2203.13779","title":"Origins of Low-dimensional Adversarial Perturbations","created":"2022-03-25","cited_by_count":4,"area":null},{"id":"2207.02093","title":"Predicting Out-of-Domain Generalization with Neighborhood Invariance","created":"2022-07-05","cited_by_count":4,"area":null},{"id":"2304.09758","title":"K-means Clustering Based Feature Consistency Alignment for Label-free Model Evaluation","created":"2023-04-17","cited_by_count":4,"area":null},{"id":"2304.13718","title":"Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models","created":"2023-04-26","cited_by_count":4,"area":null},{"id":"2308.15466","title":"Input margins can predict generalization too","created":"2023-08-29","cited_by_count":4,"area":null},{"id":"2104.03469","title":"Gi and Pal Scores: Deep Neural Network Generalization Statistics","created":"2021-04-08","cited_by_count":3,"area":null},{"id":"2105.11025","title":"Compressing Heavy-Tailed Weight Matrices for Non-Vacuous Generalization Bounds","created":"2021-05-23","cited_by_count":3,"area":null},{"id":"2401.08909","title":"Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift","created":"2024-01-17","cited_by_count":3,"area":null},{"id":"2405.05295","title":"Relevant Irrelevance: Generating Alterfactual Explanations for Image Classifiers","created":"2024-05-08","cited_by_count":3,"area":null},{"id":"2410.05248","title":"SFTMix: Elevating Language Model Instruction Tuning with Mixup Recipe","created":"2024-10-07","cited_by_count":3,"area":null},{"id":"2511.08322","title":"Mitigating Negative Flips via Margin Preserving Training","created":"2025-11-11","cited_by_count":3,"area":null},{"id":"2104.00851","title":"Estimating the Generalization in Deep Neural Networks via Sparsity","created":"2021-04-02","cited_by_count":2,"area":null},{"id":"2110.12259","title":"In Search of Probeable Generalization Measures","created":"2021-10-23","cited_by_count":2,"area":null},{"id":"2203.16723","title":"Exploiting Explainable Metrics for Augmented SGD","created":"2022-03-31","cited_by_count":2,"area":null},{"id":"2212.06461","title":"A Statistical Model for Predicting Generalization in Few-Shot Classification","created":"2022-12-13","cited_by_count":2,"area":null},{"id":"2512.04969","title":"Rethinking the Use of Vision Transformers for AI-Generated Image Detection","created":"2025-12-04","cited_by_count":2,"area":null},{"id":"2605.04358","title":"Intermediate Representations are Strong AI-Generated Image Detectors","created":"2026-05-05","cited_by_count":2,"area":null},{"id":"2102.08791","title":"Geostatistical Learning: Challenges and Opportunities","created":"2021-02-17","cited_by_count":1,"area":null},{"id":"2106.10653","title":"Practical Assessment of Generalization Performance Robustness for Deep Networks via Contrastive Examples","created":"2021-06-20","cited_by_count":1,"area":null},{"id":"2203.10366","title":"Deep Learning Generalization, Extrapolation, and Over-parameterization","created":"2022-03-19","cited_by_count":1,"area":null},{"id":"2206.05267","title":"CONTINUER: Maintaining Distributed DNN Services During Edge Failures","created":"2022-04-25","cited_by_count":1,"area":null},{"id":"2209.02881","title":"Improving Self-supervised Learning for Out-of-distribution Task via Auxiliary Classifier","created":"2022-09-07","cited_by_count":1,"area":null},{"id":"2212.03659","title":"Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural Networks","created":"2022-12-07","cited_by_count":1,"area":null},{"id":"2302.06925","title":"The Missing Margin: How Sample Corruption Affects Distance to the Boundary in ANNs","created":"2023-02-14","cited_by_count":1,"area":null},{"id":"2510.02956","title":"Confidence and Dispersity as Signals: Unsupervised Model Evaluation and Ranking","created":"2025-10-03","cited_by_count":1,"area":null},{"id":"2603.19852","title":"Failure Modes for Deep Learning-Based Online Mapping: How to Measure and Address Them","created":"2026-03-20","cited_by_count":1,"area":null},{"id":"2608.25813","title":"Mapping the Emergence of Regularization-Driven Dynamics in Grokking","created":"2026-08-26","cited_by_count":1,"area":null},{"id":"2103.00695","title":"Federated Learning without Revealing the Decision Boundaries","created":"2021-03-01","cited_by_count":0,"area":null},{"id":"2110.03999","title":"Graphs as Tools to Improve Deep Learning Methods","created":"2021-10-08","cited_by_count":0,"area":null},{"id":"2110.04519","title":"Pairwise Margin Maximization for Deep Neural Networks","created":"2021-10-09","cited_by_count":0,"area":null},{"id":"2110.08922","title":"Explaining generalization in deep learning: progress and fundamental limits","created":"2021-10-17","cited_by_count":0,"area":null},{"id":"2204.14118","title":"On the Optimization of Margin Distribution","created":"2022-04-29","cited_by_count":0,"area":null},{"id":"2303.13589","title":"On the Efficacy of Generalization Error Prediction Scoring Functions","created":"2023-03-23","cited_by_count":0,"area":null},{"id":"2309.10976","title":"Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks","created":"2023-09-20","cited_by_count":0,"area":null},{"id":"2309.10977","title":"PAGER: A Framework for Failure Analysis of Deep Regression Models","created":"2023-09-20","cited_by_count":0,"area":null},{"id":"2311.11717","title":"Can we infer the presence of Differential Privacy in Deep Learning models' weights? Towards more secure Deep Learning","created":"2023-11-20","cited_by_count":0,"area":null},{"id":"2312.16043","title":"An extended asymmetric sigmoid with Perceptron (SIGTRON) for imbalanced linear classification","created":"2023-12-26","cited_by_count":0,"area":null},{"id":"2403.05532","title":"Twin: Tuning Learning Rate and Weight Decay of Deep Homogeneous Classifiers without Validation","created":"2024-03-08","cited_by_count":0,"area":null},{"id":"2408.10474","title":"LeCov: Multi-level Testing Criteria for Large Language Models","created":"2024-08-20","cited_by_count":0,"area":null},{"id":"2410.05107","title":"Hyper-Representations: Learning from Populations of Neural Networks","created":"2024-10-07","cited_by_count":0,"area":null},{"id":"2503.00450","title":"Unsupervised Source-Free Ranking of Biomedical Segmentation Models Under Distribution Shift","created":"2025-03-01","cited_by_count":0,"area":null},{"id":"2507.23534","title":"Continual Learning with Support Boundary Experience Blending","created":"2025-07-31","cited_by_count":0,"area":null}],"next_cursor":"100"}