6 papers
Understanding Clinical Cognitive Dialogues Using Large Language Models
Vishalakshi Arumugam, Dan Schumacher, Veronica Rammouz +4
In-person cognitive assessment is both a test and an interaction. Clinicians explain tasks, repair misunderstandings, and adapt to patient responses, while patients may hesitate, s…
Detecting AI Impostors: How Do Middle Schoolers Identify LLM Agents in a Live Collaborative Setting?
Dan Schumacher, Pragathi Durga Rajarajan, Haven Kotara +6
LLMs can imitate how people write, which raises concerns about impersonation, trust, and detection in social settings. These concerns are especially important for adolescents, who…
Telling Speculative Stories to Help Humans Imagine the Harms of Healthcare AI
Xingmeng Zhao, Tongnian Wang, Dan Schumacher +2
Artificial intelligence (AI) is rapidly transforming healthcare, enabling fast development of tools like stress monitors, wellness trackers, and mental health chatbots. However, ra…
Charting the Future: Using Chart Question-Answering for Scalable Evaluation of LLM-Driven Data Visualizations
James Ford, Xingmeng Zhao, Dan Schumacher +1
We propose a novel framework that leverages Visual Question Answering (VQA) models to automate the evaluation of LLM-generated data visualizations. Traditional evaluation methods o…
RASTeR: Robust, Agentic, and Structured Temporal Reasoning
Dan Schumacher, Fatemeh Haji, Tara Grey +7
Temporal question answering (TQA) remains a challenge for large language models (LLMs), particularly when retrieved content may be irrelevant, outdated, or temporally inconsistent.…
Team UTSA-NLP at SemEval 2024 Task 5: Prompt Ensembling for Argument Reasoning in Civil Procedures with GPT4
Dan Schumacher, Anthony Rios
In this paper, we present our system for the SemEval Task 5, The Legal Argument Reasoning Task in Civil Procedure Challenge. Legal argument reasoning is an essential skill that all…