Prompt Guided Copy Mechanism for Conversational Question Answering
Yong Zhang, Zhitao Li, Jianzong Wang, Yiming Gao, Ning Cheng, Fengying, Yu, Jing Xiao

TL;DR
This paper introduces a prompt-guided copy mechanism for extractive conversational question answering, enhancing answer fluency and appropriateness by linking questions, answers, and conversation context through prompts.
Contribution
It presents a novel pluggable prompt-guided copy mechanism that improves extractive CQA by leveraging multiple prompts to guide answer extraction and editing.
Findings
Improves answer fluency and appropriateness in CQA
Achieves strong results on the CoQA benchmark
Demonstrates effectiveness of prompt-guided approach
Abstract
Conversational Question Answering (CQA) is a challenging task that aims to generate natural answers for conversational flow questions. In this paper, we propose a pluggable approach for extractive methods that introduces a novel prompt-guided copy mechanism to improve the fluency and appropriateness of the extracted answers. Our approach uses prompts to link questions to answers and employs attention to guide the copy mechanism to verify the naturalness of extracted answers, making necessary edits to ensure that the answers are fluent and appropriate. The three prompts, including a question-rationale relationship prompt, a question description prompt, and a conversation history prompt, enhance the copy mechanism's performance. Our experiments demonstrate that this approach effectively promotes the generation of natural answers and achieves good results in the CoQA challenge.
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Taxonomy
TopicsTopic Modeling · Speech and dialogue systems · Natural Language Processing Techniques
