Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension
Naoya Inoue, Harsh K. Trivedi, Steven Sinha, Niranjan Balasubramanian, Kentaro Inui · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing · 2021
How can we generate concise explanations for multi-hop Reading Comprehension (RC)?The current strategies of identifying supporting sentences can be seen as an extractive questionfocused summarization of the input text.However, these extractive explanations are not necessarily concise i.e. not minimally sufficient for answering a question.Instead, we advocate for an abstractive approach, where we propose to generate a question-focused, abstractive summary of input paragraphs and then feed it to an RC system.Given a limited amount of human-annotated abstractive explanations, we train the abstractive explainer in a semi-supervised manner, where we start from the supervised model and then train it further through trial and error maximizing a conciseness-promoted reward function.Our experiments demonstrate that the proposed abstractive explainer can generate more compact explanations than an extractive explainer with limited supervision (only 2k instances) while maintaining sufficiency.1 Our implementation is publicly available at https:// github.com/StonyBrookNLP/suqa.Charlie Rowe plays Billy Costa in a film based on what novel?[P1] [1] The Golden Compass is a 2007 British-American fantasy adventure film based on "Northern Lights", the first novel in Philip Pullman's trilogy "His Dark Materials".