46 citations · 109 across the 13 of their papers we have counts for
6 papers · 1 filter
Grow-and-Clip: Informative-yet-Concise Evidence Distillation for Answer Explanation
Yuyan Chen, Yanghua Xiao, Bang Liu
Interpreting the predictions of existing Question Answering (QA) models is critical to many real-world intelligent applications, such as QA systems for healthcare, education, and f…
Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction
Zhexue Chen, Hong Huang, Bang Liu +2
Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining…
Guiding the Growth: Difficulty-Controllable Question Generation through Step-by-Step Rewriting
Yi Cheng, Siyao Li, Bang Liu +4
This paper explores the task of Difficulty-Controllable Question Generation (DCQG), which aims at generating questions with required difficulty levels. Previous research on this ta…
Imperfect also Deserves Reward: Multi-Level and Sequential Reward Modeling for Better Dialog Management
Zhengxu Hou, Bang Liu, Ruihui Zhao +4
For task-oriented dialog systems, training a Reinforcement Learning (RL) based Dialog Management module suffers from low sample efficiency and slow convergence speed due to the spa…
GIANT: Scalable Creation of a Web-scale Ontology
Bang Liu, Weidong Guo, Di Niu +4
Understanding what online users may pay attention to is key to content recommendation and search services. These services will benefit from a highly structured and web-scale ontolo…
Asking Questions the Human Way: Scalable Question-Answer Generation from Text Corpus
Bang Liu, Haojie Wei, Di Niu +2
The ability to ask questions is important in both human and machine intelligence. Learning to ask questions helps knowledge acquisition, improves question-answering and machine rea…