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Found 4 papers, 1 papers with code
Knowledge-aware response selection with semantics underlying multi-turn open-domain conversations
Then, SemSol improves the accuracy of the response by exploiting the semantic information in a knowledge graph in accordance with the dialogue context.
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Conversational Response Selection
on Douban
Answer Generation through Unified Memories over Multiple Passages
Machine reading comprehension methods that generate answers by referring to multiple passages for a question have gained much attention in AI and NLP communities.
Can AI Generate Love Advice?: Toward Neural Answer Generation for Non-Factoid Questions
As a result, it can extract answers that suit the contexts of words used in the question as well as following the common usage of words across semantics.
Conclusion-Supplement Answer Generation for Non-Factoid Questions
This paper tackles the goal of conclusion-supplement answer generation for non-factoid questions, which is a critical issue in the field of Natural Language Processing (NLP) and Artificial Intelligence (AI), as users often require supplementary information before accepting a conclusion.
