Tree-of-Thought Prompting
Explore methods for LLMs to consider multiple reasoning paths and self-correct, enhancing complex problem-solving.
What is Tree-of-Thought (ToT)?
Welcome to Tree-of-Thought (ToT) Prompting! This advanced technique helps Large Language Models (LLMs) tackle complex problems more effectively.
Instead of a single, linear thought process, ToT allows the LLM to explore multiple reasoning paths, much like a human brainstorming different solutions.
ToT vs. Chain-of-Thought (CoT)
You might already know Chain-of-Thought (CoT), where an LLM explains its reasoning step-by-step.
- CoT is like following a single, clear path.
- ToT takes this further, allowing the LLM to branch out, consider several paths, and then choose the best one. Think of it as exploring a decision tree.
All lessons in this course
- Chain-of-Thought Prompting
- Tree-of-Thought Prompting
- Self-Consistency and Reflection