SPADER proposes step-wise peer advantage and diversity-aware exploration rewards in RL for multi-answer QA, reporting improved recall and F1 on QAMPARI, Mintaka, WebQSP, and QUEST.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , month = nov, year =
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SPADER: Step-wise Peer Advantage with Diversity-Aware Exploration Rewards for Multi-Answer Question Answering
SPADER proposes step-wise peer advantage and diversity-aware exploration rewards in RL for multi-answer QA, reporting improved recall and F1 on QAMPARI, Mintaka, WebQSP, and QUEST.