5 citations · 14 across the 8 of their papers we have counts for
8 papers
MBTI Personality Prediction for Fictional Characters Using Movie Scripts
Yisi Sang, Xiangyang Mou, Mo Yu +3
An NLP model that understands stories should be able to understand the characters in them. To support the development of neural models for this purpose, we construct a benchmark, S…
A Survey of Machine Narrative Reading Comprehension Assessments
Yisi Sang, Xiangyang Mou, Jing Li +2
As the body of research on machine narrative comprehension grows, there is a critical need for consideration of performance assessment strategies as well as the depth and scope of…
TVShowGuess: Character Comprehension in Stories as Speaker Guessing
Yisi Sang, Xiangyang Mou, Mo Yu +3
We propose a new task for assessing machines' skills of understanding fictional characters in narrative stories. The task, TVShowGuess, builds on the scripts of TV series and takes…
Efficient Long Sequence Encoding via Synchronization
Xiangyang Mou, Mo Yu, Bingsheng Yao +1
Pre-trained Transformer models have achieved successes in a wide range of NLP tasks, but are inefficient when dealing with long input sequences. Existing studies try to overcome th…
Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study
Xiangyang Mou, Chenghao Yang, Mo Yu +4
Recent advancements in open-domain question answering (ODQA), i.e., finding answers from large open-domain corpus like Wikipedia, have led to human-level performance on many datase…
Complementary Evidence Identification in Open-Domain Question Answering
Xiangyang Mou, Mo Yu, Shiyu Chang +3
This paper proposes a new problem of complementary evidence identification for open-domain question answering (QA). The problem aims to efficiently find a small set of passages tha…