Search Results for author: Scott Rome

Found 2 papers, 0 papers with code

"Ask Me Anything": How Comcast Uses LLMs to Assist Agents in Real Time

no code implementations1 May 2024 Scott Rome, Tianwen Chen, Raphael Tang, Luwei Zhou, Ferhan Ture

In this work, we introduce "Ask Me Anything" (AMA) as an add-on feature to an agent-facing customer service interface.

Language Modelling Large Language Model

Improving Content Recommendation: Knowledge Graph-Based Semantic Contrastive Learning for Diversity and Cold-Start Users

no code implementations27 Mar 2024 Yejin Kim, Scott Rome, Kevin Foley, Mayur Nankani, Rimon Melamed, Javier Morales, Abhay Yadav, Maria Peifer, Sardar Hamidian, H. Howie Huang

It is essential to provide recommendations that are both personalized and diverse, rather than solely relying on achieving high rank-based performance, such as Click-through Rate, Recall, etc.

Contrastive Learning Descriptive +4

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