5 papers
LLM-as-RNN: A Recurrent Language Model for Memory Updates and Sequence Prediction
Yuxing Lu, J. Ben Tamo, Weichen Zhao +5
Large language models are strong sequence predictors, yet standard inference relies on immutable context histories. After making an error at generation step t, the model lacks an u…
Developing Fairness-Aware Task Decomposition to Improve Equity in Post-Spinal Fusion Complication Prediction
Yining Yuan, J. Ben Tamo, Wenqi Shi +5
Fairness in clinical prediction models remains a persistent challenge, particularly in high-stakes applications such as spinal fusion surgery for scoliosis, where patient outcomes…
Leveraging Evidence-Guided LLMs to Enhance Trustworthy Depression Diagnosis
Yining Yuan, J. Ben Tamo, Micky C. Nnamdi +2
Large language models (LLMs) show promise in automating clinical diagnosis, yet their non-transparent decision-making and limited alignment with diagnostic standards hinder trust a…
MetaBench: A Multi-task Benchmark for Assessing LLMs in Metabolomics
Yuxing Lu, Xukai Zhao, J. Ben Tamo +6
Large Language Models (LLMs) have demonstrated remarkable capabilities on general text; however, their proficiency in specialized scientific domains that require deep, interconnect…
Novel Extraction of Discriminative Fine-Grained Feature to Improve Retinal Vessel Segmentation
Shuang Zeng, Chee Hong Lee, Micky C Nnamdi +9
Retinal vessel segmentation is a vital early detection method for several severe ocular diseases. Despite significant progress in retinal vessel segmentation with the advancement o…