74 citations · 265 across the 11 of their papers we have counts for
11 papers
Summaries, Highlights, and Action items: Design, implementation and evaluation of an LLM-powered meeting recap system
Sumit Asthana, Sagih Hilleli, Pengcheng He +1
Meetings play a critical infrastructural role in coordinating work. The recent surge of hybrid and remote meetings in computer-mediated spaces has led to new problems (e.g., more t…
On Improving Summarization Factual Consistency from Natural Language Feedback
Yixin Liu, Budhaditya Deb, Milagro Teruel +3
Despite the recent progress in language generation models, their outputs may not always meet user expectations. In this work, we study whether informational feedback in natural lan…
Automatically Labeling Low Quality Content on Wikipedia by Leveraging Patterns in Editing Behaviors
Sumit Asthana, Sabrina Tobar Thommel, Aaron Lee Halfaker +1
Wikipedia articles aim to be definitive sources of encyclopedic content. Yet, only 0.6% of Wikipedia articles have high quality according to its quality scale due to insufficient n…
Effects of algorithmic flagging on fairness: quasi-experimental evidence from Wikipedia
Nathan TeBlunthuis, Benjamin Mako Hill, Aaron Halfaker
Online community moderators often rely on social signals such as whether or not a user has an account or a profile page as clues that users may cause problems. Reliance on these cl…
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems
C. Estelle Smith, Bowen Yu, Anjali Srivastava +3
On Wikipedia, sophisticated algorithmic tools are used to assess the quality of edits and take corrective actions. However, algorithms can fail to solve the problems they were desi…
ORES: Lowering Barriers with Participatory Machine Learning in Wikipedia
Aaron Halfaker, R. Stuart Geiger
Algorithmic systems---from rule-based bots to machine learning classifiers---have a long history of supporting the essential work of content moderation and other curation work in p…