activity
20232025
most citedUsing Large Language Models to Generate, Validate, and Apply User Intent Taxonomies

11 citations · 21 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2025

From Measurement to Expertise: Empathetic Expert Adapters for Context-Based Empathy in Conversational AI Agents

Erfan Shayegani, Jina Suh, Andy Wilson +2

Empathy is a critical factor in fostering positive user experiences in conversational AI. While models can display empathy, it is often generic rather than tailored to specific tas…

cs.CL2025★ 2 cited

Conversational User-AI Intervention: A Study on Prompt Rewriting for Improved LLM Response Generation

Rupak Sarkar, Bahareh Sarrafzadeh, Nirupama Chandrasekaran +4

Human-LLM conversations are increasingly becoming more pervasive in peoples' professional and personal lives, yet many users still struggle to elicit helpful responses from LLM Cha…

cs.IR2024★ 6 cited

The Use of Generative Search Engines for Knowledge Work and Complex Tasks

Siddharth Suri, Scott Counts, Leijie Wang +11

Until recently, search engines were the predominant method for people to access online information. The recent emergence of large language models (LLMs) has given machines new capa…

cs.CL2024★ 2 cited

TnT-LLM: Text Mining at Scale with Large Language Models

Mengting Wan, Tara Safavi, Sujay Kumar Jauhar +11

Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and applicati…

cs.IR2023★ 11 cited

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…