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Explore a comprehensive review of the "Tree of Thoughts" paper, which introduces a novel framework for improving large language model problem-solving capabilities. Learn how this approach generalizes the Chain-of-Thought prompting method by incorporating tree search, state evaluation, and backtracking. Discover the significant improvements demonstrated in experiments on toy tasks compared to classic and Chain-of-Thought prompting. Delve into the formalization of the algorithm, its applications in games like Game of 24 and creative writing tasks, and its potential as a general problem solver. Examine the ablation studies and draw insights from the conclusion of this groundbreaking research in AI and prompt engineering.
Syllabus
- Introduction
- From Chain-of-Thought to Tree-of-Thought
- Formalizing the algorithm
- Game of 24 & Creative writing
- Crosswords
- Is this a general problem solver?
- Ablation studies
- Conclusion
Taught by
Yannic Kilcher