research / Published
Feedback is not proof.
Reading Reflexion and thinking about the gap between a useful memory and a verified result.
Reading: Reflexion: language agents with verbal reinforcement learning
Reflexion is a framework by Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. This note considers the gap between a useful reflection and a verified result.
What the paper reports
The NeurIPS 2023 paper describes agents that keep written reflections on feedback for later trials, rather than updating model weights. The authors report improvements in their evaluated tasks.
Interpretation
Store the test result alongside the explanation. A model can produce a plausible explanation without establishing the result.
Limits and open questions
The reported results do not establish that any agent memory system will improve, or that a reflection is a reliable account of what happened.
Sources and context
- Paper
- Reflexion: language agents with verbal reinforcement learning
- Paper authors
- Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, Shunyu Yao
- Read at