Publications (17)
Interview-Informed Generative Agents for Product Discovery: A Validation Study
Zichao Wang, Alexa Siu
Large language models (LLMs) have shown strong performance on standardized social science instruments, but their value for product discovery remains unclear. We investigate whether…
InfoVids: Reimagining the Viewer Experience with Alternative Visualization-Presenter Relationships
Ji Won Chung, Tongyu Zhou, Ivy Chen +7
Traditional data presentations typically separate the presenter and visualization into two separate spaces--the 3D world and a 2D screen--enforcing visualization-centric stories. T…
Toward Living Narrative Reviews: An Empirical Study of the Processes and Challenges in Updating Survey Articles in Computing Research
Raymond Fok, Alexa Siu, Daniel S. Weld
Surveying prior literature to establish a foundation for new knowledge is essential for scholarly progress. However, survey articles are resource-intensive and challenging to creat…
MODS: Moderating a Mixture of Document Speakers to Summarize Debatable Queries in Document Collections
Nishant Balepur, Alexa Siu, Nedim Lipka +4
Query-focused summarization (QFS) gives a summary of documents to answer a query. Past QFS work assumes queries have one answer, ignoring debatable ones (Is law school worth it?).…
Augmenting Expert Cognition in the Age of Generative AI: Insights from Document-Centric Knowledge Work
Alexa Siu, Raymond Fok
As Generative AI (GenAI) capabilities expand, understanding how to preserve and develop human expertise while leveraging AI's benefits becomes increasingly critical. Through empiri…
Supporting Business Document Workflows via Collection-Centric Information Foraging with Large Language Models
Raymond Fok, Nedim Lipka, Tong Sun +1
Knowledge workers often need to extract and analyze information from a collection of documents to solve complex information tasks in the workplace, e.g., hiring managers reviewing…
Experts prefer text but videos help novices: an analysis of the utility of multi-media content
Hayeong Song, Jennifer Healey, Alexa Siu +2
Multi-media increases engagement and is increasingly prevalent in online content including news, web blogs, and social media, however, it may not always be beneficial to users. To…
Imprinto: Enhancing Infrared Inkjet Watermarking for Human and Machine Perception
Martin Feick, Xuxin Tang, Raul Garcia-Martin +5
Hybrid paper interfaces leverage augmented reality to combine the desired tangibility of paper documents with the affordances of interactive digital media. Typically, virtual conte…
Optimizing Data Delivery: Insights from User Preferences on Visuals, Tables, and Text
Reuben Luera, Ryan Rossi, Franck Dernoncourt +9
In this work, we research user preferences to see a chart, table, or text given a question asked by the user. This enables us to understand when it is best to show a chart, table,…
A Survey on LLM-based Conversational User Simulation
Bo Ni, Leyao Wang, Yu Wang +27
User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary medium of human communicatio…
Survey of User Interface Design and Interaction Techniques in Generative AI Applications
Reuben Luera, Ryan A. Rossi, Alexa Siu +10
The applications of generative AI have become extremely impressive, and the interplay between users and AI is even more so. Current human-AI interaction literature has taken a broa…
Knowledge Graph Prompting for Multi-Document Question Answering
Yu Wang, Nedim Lipka, Ryan A. Rossi +3
The `pre-train, prompt, predict' paradigm of large language models (LLMs) has achieved remarkable success in open-domain question answering (OD-QA). However, few works explore this…
PDFTriage: Question Answering over Long, Structured Documents
Jon Saad-Falcon, Joe Barrow, Alexa Siu +4
Large Language Models (LLMs) have issues with document question answering (QA) in situations where the document is unable to fit in the small context length of an LLM. To overcome…
Learning to Reason in LLMs by Expectation Maximization
Junghyun Lee, Branislav Kveton, Anup Rao +4
Large language models (LLMs) solve reasoning problems by first generating a rationale and then answering. We formalize reasoning as a latent variable model and derive a reward-base…
SweeperBot: Making 3D Browsing Accessible through View Analysis and Visual Question Answering
Chen Chen, Cuong Nguyen, Alexa Siu +2
Accessing 3D models remains challenging for Screen Reader (SR) users. While some existing 3D viewers allow creators to provide alternative text, they often lack sufficient detail a…
Augmenting Textual Generation via Topology Aware Retrieval
Yu Wang, Nedim Lipka, Ruiyi Zhang +6
Despite the impressive advancements of Large Language Models (LLMs) in generating text, they are often limited by the knowledge contained in the input and prone to producing inaccu…
Quantitative LLM Judges
Aishwarya Sahoo, Jeevana Kruthi Karnuthala, Tushar Parmanand Budhwani +9
LLM-as-a-judge is a framework where a large language model (LLM) evaluates the output of another LLM. While LLMs excel at producing qualitative textual evaluations, they often stru…