1 code implementation • 19 Jan 2025 • Jing Ding, Kai Feng, Binbin Lin, Jiarui Cai, Qiushi Wang, Yu Xie, Xiaojin Zhang, Zhongyu Wei, Wei Chen
The application of large language models (LLMs) has achieved remarkable success in various fields, but their effectiveness in specialized domains like the Chinese insurance industry remains underexplored.
no code implementations • 29 Dec 2024 • Yongda Yu, Lei Zhang, Guoping Rong, Haifeng Shen, Jiahao Zhang, Haoxiang Yan, Guohao Shi, Dong Shao, Ruiqi Pan, Yuan Li, Qiushi Wang, Zhao Tian
Human evaluation confirms that both models identify issues more accurately and tend to generate review comments that better describe the issues contained in the code than the base LLMs do.
1 code implementation • 17 Dec 2024 • Yuchen Fan, Yuzhong Hong, Qiushi Wang, Junwei Bao, Hongfei Jiang, Yang song
Alignment, endowing a pre-trained Large language model (LLM) with the ability to follow instructions, is crucial for its real-world applications.
no code implementations • 9 Dec 2024 • Qiushi Wang, Yuchen Fan, Junwei Bao, Hongfei Jiang, Yang song
In recent years, Parameter-Efficient Fine-Tuning (PEFT) methods like Low-Rank Adaptation (LoRA) have significantly enhanced the adaptability of large-scale pre-trained models.
1 code implementation • 23 Oct 2023 • Wei Chen, Qiushi Wang, Zefei Long, Xianyin Zhang, Zhongtian Lu, Bingxuan Li, Siyuan Wang, Jiarong Xu, Xiang Bai, Xuanjing Huang, Zhongyu Wei
We propose Multiple Experts Fine-tuning Framework to build a financial large language model (LLM), DISC-FinLLM.
no code implementations • 13 Sep 2023 • Qiushi Wang, Xingpeng Li
An immediate need in the transmission system is to find alternative solutions that improve system operation and defer the need for new transmission lines.