2 papers
cs.CL2024
Face4RAG: Factual Consistency Evaluation for Retrieval Augmented Generation in Chinese
Yunqi Xu, Tianchi Cai, Jiyan Jiang +1
The prevailing issue of factual inconsistency errors in conventional Retrieval Augmented Generation (RAG) motivates the study of Factual Consistency Evaluation (FCE). Despite the v…
cs.CL2024
FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering
Tianchi Cai, Zhiwen Tan, Xierui Song +5
Retrieval Augmented Generation (RAG) has become prevalent in question-answering (QA) tasks due to its ability of utilizing search engine to enhance the quality of long-form questio…