Papers with question-answer matching

2 papers
One vs. Many QA Matching with both Word-level and Sentence-level Attention Network (C18-1)

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Challenge: Existing studies on question answer matching focus on formal text . however, there exists many scenarios where the QA text is informal .
Approach: They propose a novel QA matching approach using informal text from a product review site.
Outcome: The proposed approach improves word-level and sentence-level attentions for solving the noisy problem in the informal text.
Dialogizer: Context-aware Conversational-QA Dataset Generation from Textual Sources (2023.emnlp-main)

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Challenge: Existing dialog inpainting methods generate ConvQA datasets with low contextual relevance due to insufficient learning of question-answer alignment.
Approach: They propose a dialog inpainting method that generates ConvQA datasets from documents . they propose re-ranking tasks and a framework that generate contextually relevant questions .
Outcome: The proposed framework generates ConvQA datasets with high contextual relevance from textual sources.

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