5 papers
Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness
Zihan Liang, Ziwen Pan, Ruoxuan Xiong
Multimodal clinical records contain structured measurements and clinical notes recorded over time, offering rich temporal information about the evolution of patient health. Yet the…
DART: Mitigating Harm Drift in Difference-Aware LLMs via Distill-Audit-Repair Training
Ziwen Pan, Zihan Liang, Jad Kabbara +1
Large language models (LLMs) tuned for safety often avoid acknowledging demographic differences, even when such acknowledgment is factually correct (e.g., ancestry-based disease in…
Algorithmic Primitives and Compositional Geometry of Reasoning in Language Models
Samuel Lippl, Thomas McGee, Kimberly Lopez +5
How do latent and inference time computations enable large language models (LLMs) to solve multi-step reasoning? We introduce a framework for tracing and steering algorithmic primi…
Causal Representation Learning from Multimodal Clinical Records under Non-Random Modality Missingness
Zihan Liang, Ziwen Pan, Ruoxuan Xiong
Clinical notes contain rich patient information, such as diagnoses or medications, making them valuable for patient representation learning. Recent advances in large language model…
CareLab at #SMM4H-HeaRD 2025: Insomnia Detection and Food Safety Event Extraction with Domain-Aware Transformers
Zihan Liang, Ziwen Pan, Sumon Kanti Dey +1
This paper presents our system for the SMM4H-HeaRD 2025 shared tasks, specifically Task 4 (Subtasks 1, 2a, and 2b) and Task 5 (Subtasks 1 and 2). Task 4 focused on detecting mentio…