{"total":56,"rows":[{"id":"2209.02976","title":"YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications","created":"2022-09-07","cited_by_count":275,"area":null},{"id":"2210.10634","title":"RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses","created":"2022-10-12","cited_by_count":115,"area":null},{"id":"2207.09640","title":"Test-Time Adaptation via Conjugate Pseudo-labels","created":"2022-07-20","cited_by_count":98,"area":null},{"id":"2310.20199","title":"In Search of Lost Online Test-time Adaptation: A Survey","created":"2023-10-31","cited_by_count":44,"area":null},{"id":"2207.00391","title":"A Theoretical Analysis of the Learning Dynamics under Class Imbalance","created":"2022-07-01","cited_by_count":20,"area":null},{"id":"2207.02335","title":"Multi-Label Retinal Disease Classification using Transformers","created":"2022-07-05","cited_by_count":19,"area":null},{"id":"2304.10127","title":"Learning Sample Difficulty from Pre-trained Models for Reliable Prediction","created":"2023-04-20","cited_by_count":15,"area":null},{"id":"2505.11152","title":"Learning Dense Hand Contact Estimation from Imbalanced Data","created":"2025-05-16","cited_by_count":14,"area":null},{"id":"2208.13764","title":"Temporal Label Smoothing for Early Event Prediction","created":"2022-08-29","cited_by_count":12,"area":null},{"id":"2305.03515","title":"GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent","created":"2023-05-05","cited_by_count":11,"area":null},{"id":"2305.04276","title":"AdaptiveClick: Clicks-aware Transformer with Adaptive Focal Loss for Interactive Image Segmentation","created":"2023-05-07","cited_by_count":11,"area":null},{"id":"2310.04941","title":"Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line","created":"2023-10-07","cited_by_count":11,"area":null},{"id":"2503.02656","title":"Adapting Decoder-Based Language Models for Diverse Encoder Downstream Tasks","created":"2025-03-04","cited_by_count":10,"area":null},{"id":"2209.08907","title":"Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning","created":"2022-09-19","cited_by_count":9,"area":null},{"id":"2303.11562","title":"Dynamics-Aware Loss for Learning with Label Noise","created":"2023-03-21","cited_by_count":9,"area":null},{"id":"2404.18539","title":"Enhancing Boundary Segmentation for Topological Accuracy with Skeleton-based Methods","created":"2024-04-29","cited_by_count":9,"area":null},{"id":"2306.09222","title":"Stochastic Re-weighted Gradient Descent via Distributionally Robust Optimization","created":"2023-06-15","cited_by_count":6,"area":null},{"id":"2310.17159","title":"MaxEnt Loss: Constrained Maximum Entropy for Calibration under Out-of-Distribution Shift","created":"2023-10-26","cited_by_count":6,"area":null},{"id":"2305.17271","title":"Robust Lane Detection through Self Pre-training with Masked Sequential Autoencoders and Fine-tuning with Customized PolyLoss","created":"2023-05-26","cited_by_count":5,"area":null},{"id":"2210.07546","title":"Transformer-Based Speech Synthesizer Attribution in an Open Set Scenario","created":"2022-10-14","cited_by_count":4,"area":null},{"id":"2301.13247","title":"Meta-Learning Adaptive Loss Functions","created":"2023-01-30","cited_by_count":4,"area":null},{"id":"2304.05361","title":"Asymmetric Polynomial Loss For Multi-Label Classification","created":"2023-04-10","cited_by_count":4,"area":null},{"id":"2212.11542","title":"Mask Focal Loss: A unifying framework for dense crowd counting with canonical object detection networks","created":"2022-12-22","cited_by_count":3,"area":null},{"id":"2401.14107","title":"Learning under Label Noise through Few-Shot Human-in-the-Loop Refinement","created":"2024-01-25","cited_by_count":3,"area":null},{"id":"2501.15519","title":"Fuzzy-aware Loss for Source-free Domain Adaptation in Visual Emotion Recognition","created":"2025-01-26","cited_by_count":3,"area":null},{"id":"2403.08793","title":"Neural Loss Function Evolution for Large-Scale Image Classifier Convolutional Neural Networks","created":"2024-01-30","cited_by_count":2,"area":null},{"id":"2506.02393","title":"RRCANet: Recurrent Reusable-Convolution Attention Network for Infrared Small Target Detection","created":"2025-06-03","cited_by_count":2,"area":null},{"id":"2601.02543","title":"Normalized Conditional Mutual Information Surrogate Loss for Deep Neural Classifiers","created":"2026-01-05","cited_by_count":2,"area":null},{"id":"2306.14094","title":"Locally Differentially Private Distributed Online Learning with Guaranteed Optimality","created":"2023-06-25","cited_by_count":1,"area":null},{"id":"2307.05799","title":"3D Medical Image Segmentation based on multi-scale MPU-Net","created":"2023-07-11","cited_by_count":1,"area":null},{"id":"2310.05754","title":"Unleashing the power of Neural Collapse for Transferability Estimation","created":"2023-10-09","cited_by_count":1,"area":null},{"id":"2410.04084","title":"Taming the Tail: Leveraging Asymmetric Loss and Pade Approximation to Overcome Medical Image Long-Tailed Class Imbalance","created":"2024-10-05","cited_by_count":1,"area":null},{"id":"2412.13006","title":"What is YOLOv6? A Deep Insight into the Object Detection Model","created":"2024-12-17","cited_by_count":1,"area":null},{"id":"2206.02286","title":"AugLoss: A Robust Augmentation-based Fine Tuning Methodology","created":"2022-06-05","cited_by_count":0,"area":null},{"id":"2207.11637","title":"Explored An Effective Methodology for Fine-Grained Snake Recognition","created":"2022-07-24","cited_by_count":0,"area":null},{"id":"2208.00955","title":"Large-Scale Product Retrieval with Weakly Supervised Representation Learning","created":"2022-08-01","cited_by_count":0,"area":null},{"id":"2302.03488","title":"APAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model for Noisy Labels and Long-tailed Learning","created":"2023-02-06","cited_by_count":0,"area":null},{"id":"2302.09114","title":"Smoothly Giving up: Robustness for Simple Models","created":"2023-02-17","cited_by_count":0,"area":null},{"id":"2305.15424","title":"PulseNet: Deep Learning ECG-signal classification using random augmentation policy and continous wavelet transform for canines","created":"2023-05-17","cited_by_count":0,"area":null},{"id":"2305.18430","title":"Scalable and Weakly Supervised Bank Transaction Classification","created":"2023-05-28","cited_by_count":0,"area":null},{"id":"2308.00947","title":"Decomposing and Coupling Saliency Map for Lesion Segmentation in Ultrasound Images","created":"2023-08-02","cited_by_count":0,"area":null},{"id":"2407.09828","title":"Size and Smoothness Aware Adaptive Focal Loss for Small Tumor Segmentation","created":"2024-07-13","cited_by_count":0,"area":null},{"id":"2408.13214","title":"EUR-USD Exchange Rate Forecasting Based on Information Fusion with Large Language Models and Deep Learning Methods","created":"2024-08-23","cited_by_count":0,"area":null},{"id":"2409.04101","title":"Ultra-imbalanced classification guided by statistical information","created":"2024-09-06","cited_by_count":0,"area":null},{"id":"2506.16819","title":"Loupe: A Generalizable and Adaptive Framework for Image Forgery Detection","created":"2025-06-20","cited_by_count":0,"area":null},{"id":"2507.19296","title":"ABCD: Automatic Blood Cell Detection via Attention-Guided Improved YOLOX","created":"2025-07-25","cited_by_count":0,"area":null},{"id":"2602.10818","title":"Resource-Efficient RGB-Only Action Recognition for Edge Deployment","created":"2026-02-11","cited_by_count":0,"area":null},{"id":"2602.22107","title":"Don't stop me now: How Validation Criteria Affect Checkpoint Selection and Early Stopping","created":"2026-02-25","cited_by_count":0,"area":null},{"id":"2603.02533","title":"Functional Properties of the Focal-Entropy","created":"2026-03-03","cited_by_count":0,"area":null},{"id":"2604.12568","title":"Evolution-Inspired Sample Competition for Deep Neural Network Optimization","created":"2026-04-14","cited_by_count":0,"area":null},{"id":"2606.13223","title":"Distributional Loss for Robust Classification","created":"2026-06-11","cited_by_count":0,"area":null},{"id":"2606.23373","title":"Polynomial Dice Loss for Medical Image Segmentation","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2606.29471","title":"Structured Proper Loss Geometries for Multiclass Classification: Theory and Controlled Empirical Evaluation","created":"2026-06-28","cited_by_count":0,"area":null},{"id":"2607.07123","title":"Widest-Path Reachability Fields for Connectivity-Preserving Slender Structure Segmentation","created":"2026-07-08","cited_by_count":0,"area":null},{"id":"2607.16056","title":"Multi-Modal Semantic Segmentation of Electrolyzer Components for Sustainable Hydrogen Technologies: A Dual-Branch Deep Learning Approach","created":"2026-07-17","cited_by_count":0,"area":null},{"id":"2608.08207","title":"FreSH: Frequency-Segmented Hierarchical Multi-Expert Framework for Multivariate Time Series Classification","created":"2026-08-08","cited_by_count":0,"area":null}],"next_cursor":null}