Challenges and Contributing Factors in the Utilization of Large Language Models (LLMs)

no code implementations • 20 Oct 2023 • Xiaoliang Chen, Liangbin Li, Le Chang, Yunhe Huang, Yuxuan Zhao, Yuxiao Zhang, Dinuo Li

To address these issues, it's suggested to diversify training data, fine-tune models, enhance transparency and interpretability, and incorporate ethics and fairness training.

Ethics Fairness +1

Communication-efficient Byzantine-robust distributed learning with statistical guarantee

no code implementations • 28 Feb 2021 • Xingcai Zhou, Le Chang, Pengfei Xu, Shaogao Lv

To address the two issues simultaneously, this paper develops two communication-efficient and robust distributed learning algorithms for convex problems.