6 citations · 8 across the 3 of their papers we have counts for
3 papers
cs.CL2023
Optimizing Factual Accuracy in Text Generation through Dynamic Knowledge Selection
Hongjin Qian, Zhicheng Dou, Jiejun Tan +6
Language models (LMs) have revolutionized the way we interact with information, but they often generate nonfactual text, raising concerns about their reliability. Previous methods…
cs.CL2023★ 6 cited
WebBrain: Learning to Generate Factually Correct Articles for Queries by Grounding on Large Web Corpus
Hongjing Qian, Yutao Zhu, Zhicheng Dou +7
In this paper, we introduce a new NLP task -- generating short factual articles with references for queries by mining supporting evidence from the Web. In this task, called WebBrai…
cs.CL2022★ 2 cited
Coarse-to-Fine: Hierarchical Multi-task Learning for Natural Language Understanding
Zhaoye Fei, Yu Tian, Yongkang Wu +9
Generalized text representations are the foundation of many natural language understanding tasks. To fully utilize the different corpus, it is inevitable that models need to unders…