Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
When Nlp Meets LLM: Neural Approaches to Context-Based Conversational Question Answering

When Nlp Meets LLM: Neural Approaches to Context-Based Conversational Question Answering

Zaib, Munazza
Sheng, Quan Z.
Zhang, Wei Emma

Hardcover

General Computers

ISBN10: 1032970847
ISBN13: 9781032970844
Publisher: CRC Press
Published: Oct 15 2025
Pages: 102
Weight: 0.82
Height: 0.50 Width: 5.50 Depth: 8.50
Language: English

This book looks at conversational search in intelligent dialogue systems, as it investigates and addresses the challenges pertinent to effective context incorporation in conversational question answering (ConvQA). The authors explore the possibility of designing a scalable Conversational Question Answering Agent that can handle the challenges of incomplete/ambiguous questions, better able to relate to co-references to cope with the problems of effective weights and optimal threshold selection in vehicular networks. A fundamental emphasis is the understanding of ambiguous follow-up questions and the generation of contextual and question entities to fill in the missing information gaps. Key topics are studied, such as 'hard history selection' to filter out the context that is not relevant and performing a re-ranking of the selected turns based on their significance to answer the question as a part of the soft history selection process.

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