Aligner: Achieving Efficient Alignment through Weak-to-Strong Correction

no code implementations • 4 Feb 2024 • Jiaming Ji, Boyuan Chen, Hantao Lou, Donghai Hong, Borong Zhang, Xuehai Pan, Juntao Dai, Yaodong Yang

Here we introduce Aligner, a new efficient alignment paradigm that bypasses the whole RLHF process by learning the correctional residuals between the aligned and the unaligned answers.

GPT-4

AI Alignment: A Comprehensive Survey

no code implementations • 30 Oct 2023 • Jiaming Ji, Tianyi Qiu, Boyuan Chen, Borong Zhang, Hantao Lou, Kaile Wang, Yawen Duan, Zhonghao He, Jiayi Zhou, Zhaowei Zhang, Fanzhi Zeng, Kwan Yee Ng, Juntao Dai, Xuehai Pan, Aidan O'Gara, Yingshan Lei, Hua Xu, Brian Tse, Jie Fu, Stephen Mcaleer, Yaodong Yang, Yizhou Wang, Song-Chun Zhu, Yike Guo, Wen Gao

The former aims to make AI systems aligned via alignment training, while the latter aims to gain evidence about the systems' alignment and govern them appropriately to avoid exacerbating misalignment risks.

Deep learning-based rapid generation of broadly reactive antibodies against SARS-CoV-2 and its Omicron variant

1 code implementation • Cell Research 2022 • Hantao Lou, Jian-Qing Zheng, Xiaohang Leo Fang, Zhu Liang, Meihan Zhang, Yu Chen, Chunmei Wang, Xuetao Cao

The COVID-19 pandemic has been ongoing for nearly two and half years, and new variants of concern (VOCs) of SARS-CoV-2 continue to emerge, which urges the development of broadly neutralizing antibodies.

Antibody-antigen binding prediction