Evidence Piece
Evidence piece research focuses on improving the use of evidence in various AI applications, primarily aiming to enhance accuracy, trustworthiness, and explainability. Current research emphasizes developing methods for efficient evidence retrieval and selection, often employing techniques like contrastive learning, language model fine-tuning, and evidence theory, to improve fact-checking, clinical decision support, and other tasks. This work is significant because it addresses critical challenges in AI reliability and transparency, paving the way for more robust and trustworthy AI systems across diverse fields.
Papers
DetectBench: Can Large Language Model Detect and Piece Together Implicit Evidence?
Zhouhong Gu, Lin Zhang, Xiaoxuan Zhu, Jiangjie Chen, Wenhao Huang, Yikai Zhang, Shusen Wang, Zheyu Ye, Yan Gao, Hongwei Feng, Yanghua Xiao
Certified ML Object Detection for Surveillance Missions
Mohammed Belcaid, Eric Bonnafous, Louis Crison, Christophe Faure, Eric Jenn, Claire Pagetti