67 citations · 88 across the 8 of their papers we have counts for
8 papers
MaP: A Matrix-based Prediction Approach to Improve Span Extraction in Machine Reading Comprehension
Huaishao Luo, Yu Shi, Ming Gong +2
Span extraction is an essential problem in machine reading comprehension. Most of the existing algorithms predict the start and end positions of an answer span in the given corresp…
No Answer is Better Than Wrong Answer: A Reflection Model for Document Level Machine Reading Comprehension
Xuguang Wang, Linjun Shou, Ming Gong +2
The Natural Questions (NQ) benchmark set brings new challenges to Machine Reading Comprehension: the answers are not only at different levels of granularity (long and short), but a…
Tag and Correct: Question aware Open Information Extraction with Two-stage Decoding
Martin Kuo, Yaobo Liang, Lei Ji +4
Question Aware Open Information Extraction (Question aware Open IE) takes question and passage as inputs, outputting an answer tuple which contains a subject, a predicate, and one…
Mining Implicit Relevance Feedback from User Behavior for Web Question Answering
Linjun Shou, Shining Bo, Feixiang Cheng +3
Training and refreshing a web-scale Question Answering (QA) system for a multi-lingual commercial search engine often requires a huge amount of training examples. One principled id…
XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation
Yaobo Liang, Nan Duan, Yeyun Gong +21
In this paper, we introduce XGLUE, a new benchmark dataset that can be used to train large-scale cross-lingual pre-trained models using multilingual and bilingual corpora and evalu…
Enhancing Answer Boundary Detection for Multilingual Machine Reading Comprehension
Fei Yuan, Linjun Shou, Xuanyu Bai +5
Multilingual pre-trained models could leverage the training data from a rich source language (such as English) to improve performance on low resource languages. However, the transf…