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Source channel @githubtrending · Post #14737 · May 22

#other This book provides a systematic introduction to large language models (LLMs), covering topics like traditional language models, LLM architectures, prompt engineering, efficient parameter tuning, model editing, and retrieval-enhanced generation. It aims to be easy to read and rigorous, with monthly updates and a list of relevant papers. The book helps readers understand LLMs' principles and applications, making it beneficial for those interested in AI and NLP. It offers a structured learning path, which is useful for both beginners and advanced learners. https://github.com/ZJU-LLMs/Foundations-of-LLMs

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AIGC

@aigcrubbish · Post #158 · 01/27/2026, 05:06 PM

[$] Implicit arguments for BPF kfuncs Linux 内核的 kfunc 机制允许 BPF 程序直接调用内核函数。目前内核中有超过 300 个 kfunc,功能涵盖字符串处理(如 `bpf_strnlen()`)到自定义调度器(如 `scx_bpf_kick_cpu()`)等。 有时,这些 kfunc 需要访问 BPF 程序无法直接获取的上下文信息,因此无法通过参数传递。Ihor Solodrai 提交的“隐式参数”补丁集旨在解决这个问题,它允许 kfunc 隐式地接收额外的上下文参数。 原文链接:https://lwn.net/Articles/1055559/ #Linux#内核#BPF#kfunc #AIGC Read more