Can Large Language Models Understand Real-World Complex Instructions?

2 code implementations • 17 Sep 2023 • Qianyu He, Jie Zeng, Wenhao Huang, Lina Chen, Jin Xiao, Qianxi He, Xunzhe Zhou, Lida Chen, Xintao Wang, Yuncheng Huang, Haoning Ye, Zihan Li, Shisong Chen, Yikai Zhang, Zhouhong Gu, Jiaqing Liang, Yanghua Xiao

To bridge this gap, we propose CELLO, a benchmark for evaluating LLMs' ability to follow complex instructions systematically.

HistoKT: Cross Knowledge Transfer in Computational Pathology

1 code implementation • 27 Jan 2022 • Ryan Zhang, Jiadai Zhu, Stephen Yang, Mahdi S. Hosseini, Angelo Genovese, Lina Chen, Corwyn Rowsell, Savvas Damaskinos, Sonal Varma, Konstantinos N. Plataniotis

In this paper, we take a data-centric approach to the transfer learning problem and examine the existence of generalizable knowledge between histopathological datasets.

Transfer Learning

Probeable DARTS with Application to Computational Pathology

1 code implementation • 16 Aug 2021 • Sheyang Tang, Mahdi S. Hosseini, Lina Chen, Sonal Varma, Corwyn Rowsell, Savvas Damaskinos, Konstantinos N. Plataniotis, Zhou Wang

AI technology has made remarkable achievements in computational pathology (CPath), especially with the help of deep neural networks.

Neural Architecture Search

Electrical excitation and manipulation of spin-waves in spin Hall Nano-Oscillators

no code implementations • 17 Jun 2020 • Liyuan Li, Lina Chen, Ronghua Liu, Youwei Du

While in the nanogap SHNOs with strong perpendicular magnetic anisotropy (PMA), besides both nonlinear bullet soliton and propagating spin-wave mode are achieved and controlled by varying the external magnetic field and current, the magnetic bubble skyrmion mode also can be excited at a low in-plane magnetic field.

Mesoscale and Nanoscale Physics Materials Science