19 citations · 65 across the 10 of their papers we have counts for
10 papers
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs
Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan +5
The traditional Dialogue State Tracking (DST) problem aims to track user preferences and intents in user-agent conversations. While sufficient for task-oriented dialogue systems su…
Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies
Chirag Shah, Ryen W. White, Reid Andersen +13
Log data can reveal valuable information about how users interact with Web search services, what they want, and how satisfied they are. However, analyzing user intents in log data…
Toward Connecting Speech Acts and Search Actions in Conversational Search Tasks
Souvick Ghosh, Satanu Ghosh, Chirag Shah
Conversational search systems can improve user experience in digital libraries by facilitating a natural and intuitive way to interact with library content. However, most conversat…
Taking Search to Task
Chirag Shah, Ryen W. White, Paul Thomas +3
The importance of tasks in information retrieval (IR) has been long argued for, addressed in different ways, often ignored, and frequently revisited. For decades, scholars made a c…
FAIR: Fairness-Aware Information Retrieval Evaluation
Ruoyuan Gao, Yingqiang Ge, Chirag Shah
With the emerging needs of creating fairness-aware solutions for search and recommendation systems, a daunting challenge exists of evaluating such solutions. While many of the trad…
Users' Perception of Search Engine Biases and Satisfaction
Bin Han, Chirag Shah, Daniel Saelid
Search engines could consistently favor certain values over the others, which is considered as biased due to the built-in infrastructures. Many studies have been dedicated to detec…