Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering

ICLR 2018 Shuohang WangMo YuJing JiangWei ZhangXiaoxiao GuoShiyu ChangZhiguo WangTim KlingerGerald TesauroMurray Campbell

A popular recent approach to answering open-domain questions is to first search for question-related passages and then apply reading comprehension models to extract answers. Existing methods usually extract answers from single passages independently... (read more)

PDF Abstract
TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Open-Domain Question Answering Quasar Evidence Aggregation via R^3 Re-Ranking EM (Quasar-T) 42.3 # 1
F1 (Quasar-T) 49.6 # 1