Simple and Effective Text Matching with Richer Alignment Features

ACL 2019 Runqi YangJianhai ZhangXing GaoFeng JiHaiqing Chen

In this paper, we present a fast and strong neural approach for general purpose text matching applications. We explore what is sufficient to build a fast and well-performed text matching model and propose to keep three key features available for inter-sequence alignment: original point-wise features, previous aligned features, and contextual features while simplifying all the remaining components... (read more)

PDF Abstract

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Question Answering Quora Question Pairs RE2 Accuracy 89.2 % # 10