Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion-Reference-Cited by-同舟云学术

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Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion

Published:2024-05-13 Issue: Volume:631 Page:3355-3366
ISSN:
Container-title:Proceedings of the ACM Web Conference 2024
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Author:

Baek Jinheon¹^ORCID,Chandrasekaran Nirupama²^ORCID,Cucerzan Silviu²^ORCID,Herring Allen²^ORCID,Jauhar Sujay Kumar²^ORCID

Affiliation:

1. KAIST, Seoul, Republic of Korea

2. Microsoft Research, Redmond, WA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589334.3645404

Reference81 articles.

1. 2008. Spearman Rank Correlation Coefficient. 502--505.

2. 2023. Bing Search. https://www.bing.com/

3. 2023. KarmaHub. https://www.mykarmahub.com/

4. Wasi Uddin Ahmad, Kai-Wei Chang, and Hongning Wang. 2018. Multi-Task Learning for Document Ranking and Query Suggestion. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings.

5. Context Attentive Document Ranking and Query Suggestion

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