33 citations · 48 across the 6 of their papers we have counts for
6 papers
Knowledge Distillation for Enhancing Walmart E-commerce Search Relevance Using Large Language Models
Hongwei Shang, Nguyen Vo, Nitin Yadav +6
Ensuring the products displayed in e-commerce search results are relevant to users queries is crucial for improving the user experience. With their advanced semantic understanding,…
Enhancing Incremental Summarization with Structured Representations
EunJeong Hwang, Yichao Zhou, James Bradley Wendt +4
Large language models (LLMs) often struggle with processing extensive input contexts, which can lead to redundant, inaccurate, or incoherent summaries. Recent methods have used uns…
STRUM-LLM: Attributed and Structured Contrastive Summarization
Beliz Gunel, James B. Wendt, Jing Xie +4
Users often struggle with decision-making between two options (A vs B), as it usually requires time-consuming research across multiple web pages. We propose STRUM-LLM that addresse…
Simplified DOM Trees for Transferable Attribute Extraction from the Web
Yichao Zhou, Ying Sheng, Nguyen Vo +2
There has been a steady need to precisely extract structured knowledge from the web (i.e. HTML documents). Given a web page, extracting a structured object along with various attri…
FreeDOM: A Transferable Neural Architecture for Structured Information Extraction on Web Documents
Bill Yuchen Lin, Ying Sheng, Nguyen Vo +1
Extracting structured data from HTML documents is a long-studied problem with a broad range of applications like augmenting knowledge bases, supporting faceted search, and providin…
Event-Object Reasoning with Curated Knowledge Bases: Deriving Missing Information
Chitta Baral, Nguyen H. Vo
The broader goal of our research is to formulate answers to why and how questions with respect to knowledge bases, such as AURA. One issue we face when reasoning with many availabl…