SelfReflect: Unveiling LLM's Internal Reasoning for Enhanced Transparency!
Analysis
This research introduces an exciting new metric, SelfReflect, designed to enhance the transparency of Large Language Models (LLMs). By enabling LLMs to communicate their internal belief distributions, this approach promises to revolutionize how we understand and trust Generative AI.
Key Takeaways
- •Focuses on improving LLM transparency.
- •Introduces the SelfReflect metric.
- •Aims to have LLMs communicate their belief distributions.
Reference / Citation
View Original"Instead of generating a single answer and then hedging it, an LLM that is fully transparent to the user needs to be able to reflect on its internal belief distribution and output a summary of all options it deems possible, and how likely they are."
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Apple MLJan 27, 2026 00:00
* Cited for critical analysis under Article 32.