Software Engineering Limitations In Large Language Models Revealed
Large language models' reasoning abilities may be driven by retrieving relevant examples rather than true reasoning capabilities, challenging their perceived intelligence.
This is a Plain English Papers summary of a research paper called On the Brittle Foundations of ReAct Prompting for Agentic Large Language Models. If you like these kinds of analysis, you should subscribe to the AImodels.fyi newsletter or follow me on Twitter. Overview This paper examines claims about the reasoning abilities of large language models (LLMs) when using a technique called ReAct-based prompting. ReAct-based prompting is said to enhance the sequential decision-making capabilities of LLMs, but the source of this improvement is unclear. The paper systematically investigates...