马东锡NLP读书笔记
Sverige_ Dong-seok一个NLP研究员的读书笔记
| Platform |  | Pricing | Only free issues | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 9 | Subscribers | Read | sverigedongseok.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
[Formers]大语言模型是如何发展到被prompting就可以完成NLP任务的，prompt到底是什么？
本条读书笔记以从pretraining谈起，简要介绍LLM从GPT-1, BERT, BART, 到GPT-2的发展，并配合简述我最喜欢的NLP研究员Timo Schick(Toolfomer的作者)的三篇prompt-based learning的文章简要介绍prompt的演变历程。
[CoT]关于AutoGPT的疑惑, 它到底有没有CoT?
昨天发了关于AutoGPT的thread，断言它的prompt没有CoT是它的致命缺陷。 今日重新思考了这个问题，并在两位读者的指正和讨论下，重新看了AutoGPT的代码，整理了一下思考，感觉昨天的结论下的有些不严谨。 那么AutoGPT到底有没有CoT?
[CoT]从AutoGPT谈起，看大语言模型使用工具的发展
这两天，推上最热话题莫过AutoGPT。 AutoGPT的目的是让大语言模型使用外部工具（例如google）完成复杂任务，这与我最近读的论文话题一致。 此读书笔记，从AutoGPT的源码出发谈论它的局限性，以及简短地总结几篇文章来看LLM使用工具的发展。
[CoT] ReAct: 大语言模型推理，决断和行动的关键
最近大语言模型突破了文字处理任务的限制，向智能coordinator的角色转化。 一个疑问随之而来，“LLM到底如何决断并采取行动来调用不同的api的？” 本条post读书笔记，通过解读论文ReAct，同时介绍langchain的一个具体例子来试图回答这个问题。
Authors
The writers behind this newsletter.
Swedish citizen, 三流 PhD in NLP
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