ReAct: Synergizing Reasoning and Acting in Language Models
Yao et al., 2023, ReAct (The Eleventh International Conference on Learning Representations (ICLR 2023))
Subscriber deck — free during early access
1 cards in “6 Conclusion” · whole deck
6 Conclusion
- What limitations and risks of ReAct do Yao et al. note?Complex tasks with large action spaces need more demonstrations than fit in the context window, so more training data and fine-tuning are needed; and connecting language models to real actions risks retrieving private information or doing harm, which they limited by using only Wikipedia and a simulated shop.
- Yao et al., 2023, ReAct (The Eleventh International Conference on Learning Representations (ICLR 2023)), §6
Source
- Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan and Yuan Cao. 2023. ReAct: Synergizing Reasoning and Acting in Language Models. In The Eleventh International Conference on Learning Representations (ICLR 2023). https://arxiv.org/abs/2210.03629