3 papers
cs.DC2026
Democratizing LLM Training with the Edge: Challenges, Systems, and the Road Ahead
Ziyue Luo, Jiaxuan Cai, Cedric LeDenmat +27
The growing computational power of modern GPU data centers has let a few industrial giants train and deploy large language models (LLMs) on massive amounts of data. Yet the sheer s…
cs.CL2025
Fact-Controlled Diagnosis of Hallucinations in Medical Text Summarization
Suhas BN, Han-Chin Shing, Lei Xu +9
Hallucinations in large language models (LLMs) during summarization of patient-clinician dialogues pose significant risks to patient care and clinical decision-making. However, the…
cs.LG2024
Provable Meta-Learning with Low-Rank Adaptations
Jacob L. Block, Sundararajan Srinivasan, Liam Collins +2
The power of foundation models (FMs) lies in their capacity to learn highly expressive representations that can be adapted to a broad spectrum of tasks. However, these pretrained m…