Grounded and Transparent Response Generation for Conversational Information-Seeking Systems
| Title: | Grounded and Transparent Response Generation for Conversational Information-Seeking Systems |
|---|---|
| Authors: | Łajewska, Weronika |
| Publication Year: | 2024 |
| Collection: | Computer Science |
| Subject Terms: | Computer Science - Information Retrieval |
| More Details: | While previous conversational information-seeking (CIS) research has focused on passage retrieval, reranking, and query rewriting, the challenge of synthesizing retrieved information into coherent responses remains. The proposed research delves into the intricacies of response generation in CIS systems. Open-ended information-seeking dialogues introduce multiple challenges that may lead to potential pitfalls in system responses. The study focuses on generating responses grounded in the retrieved passages and being transparent about the system's limitations. Specific research questions revolve around obtaining confidence-enriched information nuggets, automatic detection of incomplete or incorrect responses, generating responses communicating the system's limitations, and evaluating enhanced responses. By addressing these research tasks the study aspires to contribute to the advancement of conversational response generation, fostering more trustworthy interactions in CIS dialogues, and paving the way for grounded and transparent systems to meet users' needs in an information-driven world. Comment: Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM '24), 2024 |
| Document Type: | Working Paper |
| DOI: | 10.1145/3616855.3635727 |
| Access URL: | http://arxiv.org/abs/2406.19281 |
| Accession Number: | edsarx.2406.19281 |
| Database: | arXiv |
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| Items | – Name: Title Label: Title Group: Ti Data: Grounded and Transparent Response Generation for Conversational Information-Seeking Systems – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Łajewska%2C+Weronika%22">Łajewska, Weronika</searchLink> – Name: DatePubCY Label: Publication Year Group: Date Data: 2024 – Name: Subset Label: Collection Group: HoldingsInfo Data: Computer Science – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Computer+Science+-+Information+Retrieval%22">Computer Science - Information Retrieval</searchLink> – Name: Abstract Label: Description Group: Ab Data: While previous conversational information-seeking (CIS) research has focused on passage retrieval, reranking, and query rewriting, the challenge of synthesizing retrieved information into coherent responses remains. The proposed research delves into the intricacies of response generation in CIS systems. Open-ended information-seeking dialogues introduce multiple challenges that may lead to potential pitfalls in system responses. The study focuses on generating responses grounded in the retrieved passages and being transparent about the system's limitations. Specific research questions revolve around obtaining confidence-enriched information nuggets, automatic detection of incomplete or incorrect responses, generating responses communicating the system's limitations, and evaluating enhanced responses. By addressing these research tasks the study aspires to contribute to the advancement of conversational response generation, fostering more trustworthy interactions in CIS dialogues, and paving the way for grounded and transparent systems to meet users' needs in an information-driven world.<br />Comment: Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM '24), 2024 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Working Paper – Name: DOI Label: DOI Group: ID Data: 10.1145/3616855.3635727 – Name: URL Label: Access URL Group: URL Data: <link linkTarget="URL" linkTerm="http://arxiv.org/abs/2406.19281" linkWindow="_blank">http://arxiv.org/abs/2406.19281</link> – Name: AN Label: Accession Number Group: ID Data: edsarx.2406.19281 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1145/3616855.3635727 Subjects: – SubjectFull: Computer Science - Information Retrieval Type: general Titles: – TitleFull: Grounded and Transparent Response Generation for Conversational Information-Seeking Systems Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Łajewska, Weronika IsPartOfRelationships: – BibEntity: Dates: – D: 27 M: 06 Type: published Y: 2024 |
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