Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Yao et al., 2023, Tree of Thoughts (Advances in Neural Information Processing Systems 36 (NeurIPS 2023))
Subscriber deck — free during early access
1 cards in “2 Background” · whole deck
2 Background
- How do IO prompting, chain-of-thought and self-consistency fall short, according to Yao et al.?IO maps input to output directly; CoT samples one chain of intermediate thoughts left to right; CoT-SC samples several chains and takes the majority answer. None explores alternative steps within a chain, and majority voting only works when the output space is small.
- Yao et al., 2023, Tree of Thoughts (Advances in Neural Information Processing Systems 36 (NeurIPS 2023)), §2
Source
- Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao and Karthik Narasimhan. 2023. Tree of Thoughts: Deliberate Problem Solving with Large Language Models. In Advances in Neural Information Processing Systems 36 (NeurIPS 2023). https://papers.nips.cc/paper_files/paper/2023/hash/271db9922b8d1f4dd7aaef84ed5ac703-Abstract-Conference.html