3 citations · 10 across the 11 of their papers we have counts for
13 papers · 1 filter
Does It Run and Is That Enough? Revisiting Text-to-Chart Generation with a Multi-Agent Approach
James Ford, Anthony Rios
Large language models can translate natural-language chart descriptions into runnable code, yet approximately 15\% of the generated scripts still fail to execute, even after superv…
UTSA-NLP at ArchEHR-QA 2025: Improving EHR Question Answering via Self-Consistency Prompting
Sara Shields-Menard, Zach Reimers, Joshua Gardner +2
We describe our system for the ArchEHR-QA Shared Task on answering clinical questions using electronic health records (EHRs). Our approach uses large language models in two steps:…
Beyond Text-to-SQL for IoT Defense: A Comprehensive Framework for Querying and Classifying IoT Threats
Ryan Pavlich, Nima Ebadi, Richard Tarbell +11
Recognizing the promise of natural language interfaces to databases, prior studies have emphasized the development of text-to-SQL systems. While substantial progress has been made…
Improving Expert Radiology Report Summarization by Prompting Large Language Models with a Layperson Summary
Xingmeng Zhao, Tongnian Wang, Anthony Rios
Radiology report summarization (RRS) is crucial for patient care, requiring concise "Impressions" from detailed "Findings." This paper introduces a novel prompting strategy to enha…
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…
Extracting Biomedical Entities from Noisy Audio Transcripts
Nima Ebadi, Kellen Morgan, Adrian Tan +5
Automatic Speech Recognition (ASR) technology is fundamental in transcribing spoken language into text, with considerable applications in the clinical realm, including streamlining…