12 citations · 33 across the 14 of their papers we have counts for
5 papers · 1 filter
Towards Faithful Explanations for Text Classification with Robustness Improvement and Explanation Guided Training
Dongfang Li, Baotian Hu, Qingcai Chen +1
Feature attribution methods highlight the important input tokens as explanations to model predictions, which have been widely applied to deep neural networks towards trustworthy AI…
A Survey of Large Language Models Attribution
Dongfang Li, Zetian Sun, Xinshuo Hu +5
Open-domain generative systems have gained significant attention in the field of conversational AI (e.g., generative search engines). This paper presents a comprehensive review of…
Enhancing Open-Domain Table Question Answering via Syntax- and Structure-aware Dense Retrieval
Nengzheng Jin, Dongfang Li, Junying Chen +2
Open-domain table question answering aims to provide answers to a question by retrieving and extracting information from a large collection of tables. Existing studies of open-doma…
Separate the Wheat from the Chaff: Model Deficiency Unlearning via Parameter-Efficient Module Operation
Xinshuo Hu, Dongfang Li, Baotian Hu +3
Large language models (LLMs) have been widely used in various applications but are known to suffer from issues related to untruthfulness and toxicity. While parameter-efficient mod…
ExplainCPE: A Free-text Explanation Benchmark of Chinese Pharmacist Examination
Dongfang Li, Jindi Yu, Baotian Hu +2
As ChatGPT and GPT-4 spearhead the development of Large Language Models (LLMs), more researchers are investigating their performance across various tasks. But more research needs t…