7 papers
Baichuan 2: Open Large-scale Language Models
Aiyuan Yang, Bin Xiao, Bingning Wang +52
Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing…
Baichuan-M1: Pushing the Medical Capability of Large Language Models
Bingning Wang, Haizhou Zhao, Huozhi Zhou +39
The current generation of large language models (LLMs) is typically designed for broad, general-purpose applications, while domain-specific LLMs, especially in vertical fields like…
HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems
Jiejun Tan, Zhicheng Dou, Wen Wang +3
Retrieval-Augmented Generation (RAG) has been shown to improve knowledge capabilities and alleviate the hallucination problem of LLMs. The Web is a major source of external knowled…
Baichuan-Omni-1.5 Technical Report
Yadong Li, Jun Liu, Tao Zhang +89
We introduce Baichuan-Omni-1.5, an omni-modal model that not only has omni-modal understanding capabilities but also provides end-to-end audio generation capabilities. To achieve f…
Baichuan Alignment Technical Report
Mingan Lin, Fan Yang, Yanjun Shen +21
We introduce Baichuan Alignment, a detailed analysis of the alignment techniques employed in the Baichuan series of models. This represents the industry's first comprehensive accou…
From Novice to Expert: LLM Agent Policy Optimization via Step-wise Reinforcement Learning
Zhirui Deng, Zhicheng Dou, Yutao Zhu +4
The outstanding capabilities of large language models (LLMs) render them a crucial component in various autonomous agent systems. While traditional methods depend on the inherent k…