activity
20222024
most cited"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models

115 citations · 296 across the 6 of their papers we have counts for

collaborators

6 papers

cs.HC202467 cited

"We Need Structured Output": Towards User-centered Constraints on Large Language Model Output

Michael Xieyang Liu, Frederick Liu, Alexander J. Fiannaca +4

Large language models can produce creative and diverse responses. However, to integrate them into current developer workflows, it is essential to constrain their outputs to follow…

cs.HC202420 cited

A Contextual Inquiry of People with Vision Impairments in Cooking

Franklin Mingzhe Li, Michael Xieyang Liu, Shaun K. Kane +1

Individuals with vision impairments employ a variety of strategies for object identification, such as pans or soy sauce, in the culinary process. In addition, they often rely on co…

cs.HC20242 cited

LLM Comparator: Visual Analytics for Side-by-Side Evaluation of Large Language Models

Minsuk Kahng, Ian Tenney, Mahima Pushkarna +7

Automatic side-by-side evaluation has emerged as a promising approach to evaluating the quality of responses from large language models (LLMs). However, analyzing the results from…

cs.HC2023115 cited

"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models

Michael Xieyang Liu, Advait Sarkar, Carina Negreanu +4

Code-generating large language models translate natural language into code. However, only a small portion of the infinite space of naturalistic utterances is effective at guiding c…

cs.HC202262 cited

Wigglite: Low-cost Information Collection and Triage

Michael Xieyang Liu, Andrew Kuznetsov, Yongsung Kim +3

Consumers conducting comparison shopping, researchers making sense of competitive space, and developers looking for code snippets online all face the challenge of capturing the inf…

cs.HC202230 cited

Freedom to Choose: Understanding Input Modality Preferences of People with Upper-body Motor Impairments for Activities of Daily Living

Franklin Mingzhe Li, Michael Xieyang Liu, Yang Zhang +1

Many people with upper-body motor impairments encounter challenges while performing Activities of Daily Living (ADLs) and Instrumental Activities of Daily Living (IADLs), such as t…