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【BAYES COFFEE HOUSE TECH TALK SERIES】From Generalized to Personalized: Leveraging LLMs for Conversational Search

Dr. Shubham Chatterjee from the University of Edinburgh will give a talk, in person and online, for the Coffee House Tech Talk Series. Details of the talk are below.

Title: From Generalized to Personalized: Leveraging LLMs for Conversational Search

Speaker: Dr. Shubham Chatterjee

                     University of Edinburgh

When: 11am Tue 21 May (UTC+00:00)London

Where: 4th floor Bayes Centre


Title: Tech Talk 0521-From Generalized to Personalized: Leveraging LLMs for Conversational Search

Time: 05/21(Tues) 11:00-12:00 (UTC+01:00)London


Meeting ID95845941



Personalization is paramount for conversational search and recommendation. Despite

significant advancements in Large Language Models (LLMs), these models often provide

generalized recommendations that fail to capture the nuanced interests of individual users.

To be effective, conversational agents must not only address users’ immediate queries but

also adapt their responses based on the cumulative context of interactions.

A major challenge in developing personalized conversational systems is the lack of

large-scale datasets that reflect genuine user preferences and interactions. In this talk, I will

first introduce a method for collecting extensive, multi-session, multi-domain,

human-written personal conversations using LLMs.

Following this, I will provide an overview of the TREC Interactive Knowledge Assistance

track, which I am co-leading with NIST in the US, aimed at advancing research in

personalized conversational search.


Dr. Shubham Chatterjee is a Postdoctoral Research Associate working with Dr. Jeff Dalton in

the Generalized Representation and Information Learning (GRILL) Lab, a leading research

group in the School of Informatics at the University of Edinburgh. Dr. Chatterjee’s research

focuses on developing neural information retrieval models that leverage Knowledge Graph

semantics to enhance the understanding and addressing of users’ information needs. His work

intersects the fields of Information Retrieval and Natural Language Processing (NLP),

employing Deep Learning to refine information access systems. Currently, Dr. Chatterjee is

engaged in research on personalized conversational assistants, Large Language Models

(LLMs), and their applications in search.

Prior to this, Dr. Chatterjee was a Postdoctoral Research Associate with Dr. Jeff Dalton at the

University of Glasgow, Scotland, as part of the prestigious Glasgow IR group. He also worked

as a Postdoctoral Research Associate with Dr. Laura Dietz at the University of New Hampshire,

Durham, USA, where he completed his PhD under her supervision.


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