Partner Event - From Generalized to Personalized: Leveraging LLMs for Conversational Search About the event Abstract 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 Assistancetrack, which I am co-leading with NIST in the US, aimed at advancing research in personalized conversational search. Speaker Bio 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. May 21 2024 11.00 - 12.00 Partner Event - From Generalized to Personalized: Leveraging LLMs for Conversational Search Join Huawei and Dr. Shubham Chatterjee for their next tech talk, taking place on 21 May 2024. 4th floor Bayes Centre https://app.huawei.com/wmeeting/join/95845941/kb05G3fTFrqWZiOAny2Pk3trMdB88MZG1 Meeting ID：95845941 Passcode：649510 Register
Partner Event - From Generalized to Personalized: Leveraging LLMs for Conversational Search About the event Abstract 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 Assistancetrack, which I am co-leading with NIST in the US, aimed at advancing research in personalized conversational search. Speaker Bio 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. May 21 2024 11.00 - 12.00 Partner Event - From Generalized to Personalized: Leveraging LLMs for Conversational Search Join Huawei and Dr. Shubham Chatterjee for their next tech talk, taking place on 21 May 2024. 4th floor Bayes Centre https://app.huawei.com/wmeeting/join/95845941/kb05G3fTFrqWZiOAny2Pk3trMdB88MZG1 Meeting ID：95845941 Passcode：649510 Register
May 21 2024 11.00 - 12.00 Partner Event - From Generalized to Personalized: Leveraging LLMs for Conversational Search Join Huawei and Dr. Shubham Chatterjee for their next tech talk, taking place on 21 May 2024.
