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Yi-Lightning Technical Report

2 December 2024
01. AI
:
Alan Wake
Albert Wang
Bei Chen
Chuancheng Lv
Chao Li
Chengen Huang
Chenglin Cai
Chujie Zheng
Daniel Cooper
Ethan Dai
Fan Zhou
Feng Hu
Heng Ji
Howard Qiu
Jiangcheng Zhu
Jun Tian
Katherine Su
Lefei Zhang
Liying Li
Ming Song
Mou Li
Peng Liu
Qichen Hu
Shawn Wang
Shijun Zhou
Shiyong Li
Tianhang Zhu
Wen Xie
Xiang He
Xiusi Chen
Xiaohui Hu
Xiaoyi Ren
Xinyao Niu
Yongqian Li
Yongke Zhao
Yongzhen Luo
Y. Xu
Yuxuan Sha
Zhaodong Yan
Zhiyuan Liu
Zirui Zhang
    OSLM
ArXiv (abs)PDFHTML
Abstract

This technical report presents Yi-Lightning, our latest flagship large language model (LLM). It achieves exceptional performance, ranking 6th overall on Chatbot Arena, with particularly strong results (2nd to 4th place) in specialized categories including Chinese, Math, Coding, and Hard Prompts. Yi-Lightning leverages an enhanced Mixture-of-Experts (MoE) architecture, featuring advanced expert segmentation and routing mechanisms coupled with optimized KV-caching techniques. Our development process encompasses comprehensive pre-training, supervised fine-tuning (SFT), and reinforcement learning from human feedback (RLHF), where we devise deliberate strategies for multi-stage training, synthetic data construction, and reward modeling. Furthermore, we implement RAISE (Responsible AI Safety Engine), a four-component framework to address safety issues across pre-training, post-training, and serving phases. Empowered by our scalable super-computing infrastructure, all these innovations substantially reduce training, deployment and inference costs while maintaining high-performance standards. With further evaluations on public academic benchmarks, Yi-Lightning demonstrates competitive performance against top-tier LLMs, while we observe a notable disparity between traditional, static benchmark results and real-world, dynamic human preferences. This observation prompts a critical reassessment of conventional benchmarks' utility in guiding the development of more intelligent and powerful AI systems for practical applications. Yi-Lightning is now available through our developer platform at https://platform.lingyiwanwu.com.

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