18 citations · 21 across the 3 of their papers we have counts for
3 papers
cs.CL2022
Feeding What You Need by Understanding What You Learned
Xiaoqiang Wang, Bang Liu, Fangli Xu +3
Machine Reading Comprehension (MRC) reveals the ability to understand a given text passage and answer questions based on it. Existing research works in MRC rely heavily on large-si…
cs.CL2021★ 3 cited
Graph-augmented Learning to Rank for Querying Large-scale Knowledge Graph
Hanning Gao, Lingfei Wu, Po Hu +3
Knowledge graph question answering (KGQA) based on information retrieval aims to answer a question by retrieving answer from a large-scale knowledge graph. Most existing methods fi…
cs.AI2020★ 18 cited
QBSUM: a Large-Scale Query-Based Document Summarization Dataset from Real-world Applications
Mingjun Zhao, Shengli Yan, Bang Liu +6
Query-based document summarization aims to extract or generate a summary of a document which directly answers or is relevant to the search query. It is an important technique that…