🚀 The Knowing-Saying Gap: When Probes See Errors that Confidence Misses
Do LLMs "know" they are making a mistake before they even say it? 🤖 The "Knowing-Saying Gap" reveals a fascinating disconnect: language models detect internal errors with near-perfect accuracy, yet still output confident falsehoods. Here is how: 👇
Key insights from the paper:
• Linear probes can detect corrupted contexts in LLMs with near-perfect accuracy.
• This internal "awareness" does NOT translate into reliable confidence scores.
• LLMs can remain highly confident externally despite internal error detection.
How can we bridge this gap between what LLMs "know" internally and what they actually output? Is listening to an AI's "inner voice" the key to safer deployment? Let us know your thoughts! 💬
🔗 Read Full Original Story Here
Automated developer update powered by Nexlyi AI Dashboard.
Top comments (0)