115 citations · 332 across the 8 of their papers we have counts for
8 papers
Selenite: Scaffolding Online Sensemaking with Comprehensive Overviews Elicited from Large Language Models
Michael Xieyang Liu, Tongshuang Wu, Tianying Chen +3
Sensemaking in unfamiliar domains can be challenging, demanding considerable user effort to compare different options with respect to various criteria. Prior research and our forma…
"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…
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…
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…
Crystalline: Lowering the Cost for Developers to Collect and Organize Information for Decision Making
Michael Xieyang Liu, Aniket Kittur, Brad A. Myers
Developers perform online sensemaking on a daily basis, such as researching and choosing libraries and APIs. Prior research has introduced tools that help developers capture inform…
Understanding How Programmers Can Use Annotations on Documentation
Amber Horvath, Michael Xieyang Liu, River Hendriksen +5
Modern software development requires developers to find and effectively utilize new APIs and their documentation, but documentation has many well-known issues. Despite this, develo…
To Reuse or Not To Reuse? A Framework and System for Evaluating Summarized Knowledge
Michael Xieyang Liu, Aniket Kittur, Brad A. Myers
As the amount of information online continues to grow, a correspondingly important opportunity is for individuals to reuse knowledge which has been summarized by others rather than…
Learning to Detect Human-Object Interactions
Yu-Wei Chao, Yunfan Liu, Xieyang Liu +2
We study the problem of detecting human-object interactions (HOI) in static images, defined as predicting a human and an object bounding box with an interaction class label that co…