Category: chain-of-thought
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Recap of all types of LLM Agents
Recap of all types of LLM Agents Regular, ReAct, Chain-of-Thought, Reflexion, ToT, GoT, PoT The post Recap of all types of LLM Agents appeared first on Towards Data Science. Mauro Di Pietro Go to original source
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Tree of Thought Prompting: Teaching LLMs to Think Slowly
Tree of Thought Prompting: Teaching LLMs to Think Slowly Playing Minesweeper with Augmented Reasoning The post Tree of Thought Prompting: Teaching LLMs to Think Slowly appeared first on Towards Data Science. Shuyang Go to original source
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Empowering LLMs to Think Deeper by Erasing Thoughts
Empowering LLMs to Think Deeper by Erasing Thoughts Introduction Recent large language models (LLMs) — such as OpenAI’s o1/o3, DeepSeek’s R1 and Anthropic’s Claude 3.7 — demonstrate that allowing the model to think deeper and longer at test time can significantly enhance model’s reasoning capability. The core approach underlying their deep thinking capability is called…
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Building a Custom AI Jira Agent
Building a Custom AI Jira Agent How I used Google Mesop, Django, LangChain Agents, CO-STAR & Chain-of-Thought (CoT) prompting combined with the Jira API to better automate Jira Photo by Google DeepMind on Unsplash The inspiration for this project came from hosting a Jira ticket creation tool on a web application I had developed for internal users.…