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Beyond Words: A Mathematical Framework for Interpreting Large Language Models
Large language models (LLMs) are powerful AI tools that can generate and comprehend natural language text and other complex information.
Exploring the Boundaries of GPT-4 in Radiology
In this paper, we focus on assessing the performance of GPT-4, the most capable LLM so far, on the text-based applications for radiology reports, comparing against state-of-the-art (SOTA) radiology-specific models.
Robustness of Neural Networks: A Probabilistic and Practical Approach
Our algorithm uses abstract interpretation to approximate the behavior of a neural network and compute an overapproximation of the input regions that violate robustness.
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