On the Calibration of Pre-trained Language Models using Mixup Guided by
Area Under the Margin and Saliency

On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency

14 March 2022

Cornelia Caragea

Papers citing "On the Calibration of Pre-trained Language Models using Mixup Guided by Area Under the Margin and Saliency"

8 / 8 papers shown

Title
Comparing Uncertainty Measurement and Mitigation Methods for Large Language Models: A Systematic Review Toghrul Abbasli Kentaroh Toyoda Yuan Wang Leon Witt Muhammad Asif Ali Yukai Miao Dan Li Qingsong Wei UQCV 94 0 0 25 Apr 2025
Large Language Model Confidence Estimation via Black-Box Access Tejaswini Pedapati Amit Dhurandhar Soumya Ghosh Soham Dan P. Sattigeri 89 3 0 21 Feb 2025
Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback Katherine Tian E. Mitchell Allan Zhou Archit Sharma Rafael Rafailov Huaxiu Yao Chelsea Finn Christopher D. Manning 66 289 0 24 May 2023
Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks Haoqi Zheng Qihuang Zhong Liang Ding Zhiliang Tian Xin-Yi Niu Dongsheng Li Dacheng Tao VLM 43 6 0 22 May 2023
Bag of Tricks for In-Distribution Calibration of Pretrained Transformers Jaeyoung Kim Dongbin Na Sungchul Choi Sungbin Lim VLM 38 5 0 13 Feb 2023
A Survey of Mix-based Data Augmentation: Taxonomy, Methods, Applications, and Explainability Chengtai Cao Fan Zhou Yurou Dai Jianping Wang Kunpeng Zhang AAML 24 28 0 21 Dec 2022
Calibration Meets Explanation: A Simple and Effective Approach for Model Confidence Estimates Dongfang Li Baotian Hu Qingcai Chen 16 8 0 06 Nov 2022
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 246 290 0 17 Mar 2020