5 papers
Generalist Foundation Models Are Not Clinical Enough for Hospital Operations
Lavender Y. Jiang, Angelica Chen, Xu Han +16
Hospitals and healthcare systems rely on operational decisions that determine patient flow, cost, and quality of care. Despite strong performance on medical knowledge and conversat…
Enhancing LLM-based Fault Localization with a Functionality-Aware Retrieval-Augmented Generation Framework
Xinyu Shi, Zhenhao Li, An Ran Chen
Fault localization (FL) is a critical but time-consuming task in software debugging, aiming to identify faulty code elements. While recent advances in large language models (LLMs)…
Bridging Offline and Online Reinforcement Learning for LLMs
Jack Lanchantin, Angelica Chen, Janice Lan +9
We investigate the effectiveness of reinforcement learning methods for finetuning large language models when transitioning from offline to semi-online to fully online regimes for b…
Unifying Block-wise PTQ and Distillation-based QAT for Progressive Quantization toward 2-bit Instruction-Tuned LLMs
Jung Hyun Lee, Seungjae Shin, Vinnam Kim +2
As the rapid scaling of large language models (LLMs) poses significant challenges for deployment on resource-constrained devices, there is growing interest in extremely low-bit qua…
Diverse Preference Optimization
Jack Lanchantin, Angelica Chen, Shehzaad Dhuliawala +4
Post-training of language models, either through reinforcement learning, preference optimization or supervised finetuning, tends to sharpen the output probability distribution and…