4 papers
CRAFT: LLM-Based Iterative Refinement for Temporal Reasoning over Clinical Narratives
Chengyang He, Tahreem Arif, Marko Zivkovic +3
Understanding the temporal progression of symptoms in clinical narratives is critical for disease monitoring, safety surveillance, and causality assessment. Clinical narratives, ho…
GRAIN: Group Aggregation via Min-Norm Objective
Nghia Bui, Jiarui Yao, Lijing Wang
Learning instability is a long-standing problem across machine learning, but it is especially acute in the overparameterized regime that defines modern deep learning: large models…
Light-FMP: Lightweight Feature and Model Pruning for Enhanced Deep Recommender Systems
Nghia Bui, Yue Ning, Lijing Wang
Deep recommender systems (DRS) often face challenges in balancing computational efficiency and model accuracy, especially when handling high-dimensional input features. Existing me…
Assessing the Macro and Micro Effects of Random Seeds on Fine-Tuning Large Language Models
Nghia Bui, Guergana Savova, Lijing Wang
The impact of random seeds in fine-tuning large language models (LLMs) has been largely overlooked despite its potential influence on model performance.In this study, we systematic…