3 citations · 7 across the 6 of their papers we have counts for
5 papers · 1 filter
An Expert Schema for Evaluating Large Language Model Errors in Scholarly Question-Answering Systems
Anna Martin-Boyle, William Humphreys, Martha Brown +2
Large Language Models (LLMs) are transforming scholarly tasks like search and summarization, but their reliability remains uncertain. Current evaluation metrics for testing LLM rel…
PaperTrail: A Claim-Evidence Interface for Grounding Provenance in LLM-based Scholarly Q&A
Anna Martin-Boyle, Cara A. C. Leckey, Martha C. Brown +1
Large language models (LLMs) are increasingly used in scholarly question-answering (QA) systems to help researchers synthesize vast amounts of literature. However, these systems of…
Unraveling Entangled Feeds: Rethinking Social Media Design to Enhance User Well-being
Ashlee Milton, Dan Runningen, Loren Terveen +2
Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We present findings from design works…
Opportunities and Barriers for AI Feedback on Meeting Inclusion in Socioorganizational Teams
Mo Houtti, Moyan Zhou, Daniel Runningen +5
Inclusion is important for meeting effectiveness, which is in turn central to organizational functioning. One way of improving inclusion in meetings is through feedback, but social…
Wisdom of the Crowd, Without the Crowd: A Socratic LLM for Asynchronous Deliberation on Perspectivist Data
Malik Khadar, Daniel Runningen, Julia Tang +2
Data annotation underpins the success of modern AI, but the aggregation of crowd-collected datasets can harm the preservation of diverse perspectives in data. Difficult and ambiguo…