Search Results for author: Xiangyang Mou

Found 8 papers, 3 papers with code

A Survey of Machine Narrative Reading Comprehension Assessments

no code implementations30 Apr 2022 Yisi Sang, Xiangyang Mou, Jing Li, Jeffrey Stanton, Mo Yu

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 different benchmark tasks.

Reading Comprehension

TVShowGuess: Character Comprehension in Stories as Speaker Guessing

1 code implementation NAACL 2022 Yisi Sang, Xiangyang Mou, Mo Yu, Shunyu Yao, Jing Li, Jeffrey Stanton

We propose a new task for assessing machines' skills of understanding fictional characters in narrative stories.

Efficient Long Sequence Encoding via Synchronization

no code implementations15 Mar 2022 Xiangyang Mou, Mo Yu, Bingsheng Yao, Lifu Huang

Pre-trained Transformer models have achieved successes in a wide range of NLP tasks, but are inefficient when dealing with long input sequences.

Narrative Question Answering with Cutting-Edge Open-Domain QA Techniques: A Comprehensive Study

3 code implementations7 Jun 2021 Xiangyang Mou, Chenghao Yang, Mo Yu, Bingsheng Yao, Xiaoxiao Guo, Saloni Potdar, Hui Su

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 datasets.

Open-Domain Question Answering

Multimodal Dialogue State Tracking By QA Approach with Data Augmentation

no code implementations20 Jul 2020 Xiangyang Mou, Brandyn Sigouin, Ian Steenstra, Hui Su

Different from purely text-based dialogue state tracking, the dialogue in AVSD contains a sequence of question-answer pairs about a video and the final answer to the given question requires additional understanding of the video.

Data Augmentation Dialogue State Tracking +2

Frustratingly Hard Evidence Retrieval for QA Over Books

no code implementations WS 2020 Xiangyang Mou, Mo Yu, Bingsheng Yao, Chenghao Yang, Xiaoxiao Guo, Saloni Potdar, Hui Su

A lot of progress has been made to improve question answering (QA) in recent years, but the special problem of QA over narrative book stories has not been explored in-depth.

Question Answering Retrieval

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