Direct Confidence Alignment: Aligning Verbalized Confidence with Internal Confidence In Large Language Models
Published:Dec 12, 2025 19:29
•1 min read
•ArXiv
Analysis
This article focuses on improving the reliability of Large Language Models (LLMs) by ensuring the confidence expressed by the model aligns with its internal certainty. This is a crucial step towards building more trustworthy and dependable AI systems. The research likely explores methods to calibrate the model's output confidence, potentially using techniques to map internal representations to verbalized confidence levels. The source, ArXiv, suggests this is a pre-print, indicating ongoing research.
Key Takeaways
- •Focuses on aligning verbalized confidence with internal confidence in LLMs.
- •Aims to improve the trustworthiness and dependability of AI systems.
- •Likely explores methods for calibrating model output confidence.
Reference
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