collaborators

5 papers

cs.CL2026

Graph Alignment Topology as an Inductive Bias for Grounding Detection

Paul Landes, Pranav Herur, Adam Cross +1

Large Language Models (LLMs) are optimized to produce distributionally plausible continuations rather than to explicitly verify whether generated propositions are entailed by sourc…

cs.LG2026

PyHealth 2.0: A Comprehensive Open-Source Toolkit for Accessible and Reproducible Clinical Deep Learning

John Wu, Yongda Fan, Zhenbang Wu +14

Difficulty replicating baselines, high computational costs, and required domain expertise create persistent barriers to clinical AI research. To address these challenges, we introd…

cs.LG2025

Social Determinants of Health Prediction for ICD-9 Code with Reasoning Models

Sharim Khan, Paul Landes, Adam Cross +1

Social Determinants of Health correlate with patient outcomes but are rarely captured in structured data. Recent attention has been given to automatically extracting these markers…

cs.CL2025

Enhancing Clinical Models with Pseudo Data for De-identification

Paul Landes, Aaron J Chaise, Tarak Nath Nandi +1

Many models are pretrained on redacted text for privacy reasons. Clinical foundation models are often trained on de-identified text, which uses special syntax (masked) text in plac…

cs.CL2025

Integration of Large Language Models and Traditional Deep Learning for Social Determinants of Health Prediction

Paul Landes, Jimeng Sun, Adam Cross

Social Determinants of Health (SDoH) are economic, social and personal circumstances that affect or influence an individual's health status. SDoHs have shown to be correlated to we…