5 papers
DASH: Dual-View Self-Distillation with Multi-Layer Hidden Representations for Robust Speech Recognition
Jaeeun Baik, Ui-Hyeop Shin, Jiwoon Lee +2
Automatic Speech Recognition (ASR) often degrades in real-world noisy environments, making noise robustness essential for deployment. Supervised noise-augmented fine-tuning is a co…
From Promising Capability to Pervasive Bias: Assessing Large Language Models for Emergency Department Triage
Joseph Lee, Tianqi Shang, Jae Young Baik +4
Large Language Models (LLMs) have shown promise in clinical decision support, yet their application to triage remains underexplored. We systematically investigate the capabilities…
Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models
Joseph Lee, Shu Yang, Jae Young Baik +8
Predicting phenotypes with complex genetic bases based on a small, interpretable set of variant features remains a challenging task. Conventionally, data-driven approaches are util…
Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications
Shu Yang, Nhat Truong Pham, Ziyang Li +10
Due to the hierarchical organization of RNA structures and their pivotal roles in fulfilling RNA functions, the formation of RNA secondary structure critically influences many biol…
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature
Dawei Li, Shu Yang, Zhen Tan +10
Recent advancements in large language models (LLMs) have achieved promising performances across various applications. Nonetheless, the ongoing challenge of integrating long-tail kn…