label smoothing

CSECU-DSG at SemEval-2026 Task 10: Fine-Tuning DeBERTa Transformer Model for Conspiracy Detection SemEval 2026 CURA: Clinical Uncertainty Risk Alignment for Language Model–Based Risk Prediction ACL 2026 HierUQ: Hierarchical Uncertainty Quantification with Adaptive Granularity Reconciliation for Degraded Image Classification CVPR 2026 Improving Sparse IMU-based Motion Capture with Motion Label Smoothing AAAI 2026 Investigating the Multilingual Calibration Effects of Language Model Instruction Tuning EACL 2026 pfr821 at SemEval-2026 Task 9: Multilingual Polarization Detection via Hybrid XLM-RoBERTa with Targeted Data Augmentation and Imbalance-Aware Training SemEval 2026 Posterior Label Smoothing for Node Classification AAAI 2026 Segmentation Fault at SemEval-2026 Task 13: A Regularization-First Approach with Generator-Based Out-of-Distribution Splits for Detecting AI-Generated Code SemEval 2026 Sujith Kanakkassery at AbjadMed: Imbalance-Aware Transformer Fine-tuning for Arabic Medical Text Classification EACL 2026 Calibrated Language Models and How to Find Them with Label Smoothing ICML 2025 CaliMatch: Adaptive Calibration for Improving Safe Semi-supervised Learning ICCV 2025 For Better or For Worse? Learning Minimum Variance Features With Label Augmentation ICLR 2025 GRAM: A Generative Foundation Reward Model for Reward Generalization ICML 2025 Mitigating Catastrophic Overfitting in Fast Adversarial Training via Label Information Elimination ICCV 2025 Regularizing Hard Examples Improves Adversarial Robustness JMLR 2025 RepFace: Refining Closed-Set Noise with Progressive Label Correction for Face Recognition AAAI 2025 Robust Classification by Coupling Data Mollification with Label Smoothing AISTATS 2025 Teacher-Free Knowledge Distillation for Improving Short-Utterance Spoken Language Identification Interspeech 2025 Towards Understanding Why Label Smoothing Degrades Selective Classification and How to Fix It ICLR 2025 Training Deep Neural Networks with Virtual Smoothing Classes AAAI 2025 Uncertainty-Based Data-Wise Label Smoothing for Calibrating Multiple Instance Learning in Histopathology Image Classification WACV 2025 Annealing Self-Distillation Rectification Improves Adversarial Training ICLR 2024 AutoAugment Is What You Need: Enhancing Rule-based Augmentation Methods in Low-resource Regimes EACL 2024 Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks ICLR 2024 DC-MBR: Distributional Cooling for Minimum Bayesian Risk Decoding COLING 2024