2 citations · 2 across the 2 of their papers we have counts for
8 papers
What Prompts Don't Say: Understanding and Managing Underspecification in LLM Prompts
Chenyang Yang, Yike Shi, Qianou Ma +3
Prompt underspecification is a common challenge when interacting with LLMs. In this paper, we present an in-depth analysis of this problem, showing that while LLMs can often infer…
Compass vs Railway Tracks: Unpacking User Mental Models for Communicating Long-Horizon Work to Humans vs. AI
Savvas Petridis, Michael Xieyang Liu, Alexander J. Fiannaca +2
As AI systems grow increasingly capable of operating for hours or days at a time, users' prompts are transforming into elaborate specifications for the AI to autonomously work on.…
ADCanvas: Accessible and Conversational Audio Description Authoring for Blind and Low Vision Creators
Franklin Mingzhe Li, Michael Xieyang Liu, Cynthia L. Bennett +1
Audio Description (AD) provides essential access to visual media for blind and low vision (BLV) audiences. Yet current AD production tools remain largely inaccessible to BLV video…
AI LEGO: Scaffolding Cross-Functional Collaboration in Industrial Responsible AI Practices during Early Design Stages
Muzhe Wu, Yanzhi Zhao, Shuyi Han +2
Responsible AI (RAI) efforts increasingly emphasize the importance of addressing potential harms early in the AI development lifecycle through social-technical lenses. However, in…
Gensors: Authoring Personalized Visual Sensors with Multimodal Foundation Models and Reasoning
Michael Xieyang Liu, Savvas Petridis, Vivian Tsai +4
Multimodal large language models (MLLMs), with their expansive world knowledge and reasoning capabilities, present a unique opportunity for end-users to create personalized AI sens…
The Evolution of LLM Adoption in Industry Data Curation Practices
Crystal Qian, Michael Xieyang Liu, Emily Reif +7
As large language models (LLMs) grow increasingly adept at processing unstructured text data, they offer new opportunities to enhance data curation workflows. This paper explores t…