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20232025
most citedCorpusStudio: Surfacing Emergent Patterns in a Corpus of Prior Work while Writing

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

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cs.HC2025

Interface Design to Support Legal Reading and Writing: Insights from Interviews with Legal Experts

Chelse Swoopes, Ziwei Gu, Elena L. Glassman

Legal professionals spend significant time reading, writing, and interpreting complex documents, yet research has not fully captured how they approach these tasks or what they expe…

cs.HC2025

The Impact of Revealing Large Language Model Stochasticity on Trust, Reliability, and Anthropomorphization

Chelse Swoopes, Tyler Holloway, Elena L. Glassman

Interfaces for interacting with large language models (LLMs) are often designed to mimic human conversations, typically presenting a single response to user queries. This design ch…

cs.HC20254 cited

CorpusStudio: Surfacing Emergent Patterns in a Corpus of Prior Work while Writing

Hai Dang, Chelse Swoopes, Daniel Buschek +1

Many communities, including the scientific community, develop implicit writing norms. Understanding them is crucial for effective communication with that community. Writers gradual…

cs.HC2024

Supporting Sensemaking of Large Language Model Outputs at Scale

Katy Ilonka Gero, Chelse Swoopes, Ziwei Gu +2

Large language models (LLMs) are capable of generating multiple responses to a single prompt, yet little effort has been expended to help end-users or system designers make use of…

cs.HC2023

ChainForge: A Visual Toolkit for Prompt Engineering and LLM Hypothesis Testing

Ian Arawjo, Chelse Swoopes, Priyan Vaithilingam +2

Evaluating outputs of large language models (LLMs) is challenging, requiring making -- and making sense of -- many responses. Yet tools that go beyond basic prompting tend to requi…