Apple Research: Uncertainty Quantification for LLM Function Calling
Apple ML Research · rss · 2026-07-15
Apple ML Research discusses **Uncertainty Quantification (UQ) for LLM Function-Calling**. The article points out that LLMs are increasingly used to autonomously execute real-world tasks, and errors in function calling can have severe consequences, such as transferring funds or deleting data. Therefore, before executing a function call, it's crucial to assess the model's confidence in whether it can correctly complete the task. This work focuses on: - Why function calling needs UQ - How to determine if a model is reliable enough before making a call - The goal is to reduce the irreversible risks associated with erroneous tool calls
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