Undergraduate Research & Scholarships

Noam Michael

Hallucination Detection in LLMs through Confidence Calibration

As Large Language Models (LLMs) like ChatGPT become more widespread, their tendency to generate inaccurate or fabricated information has emerged as a significant concern. To reduce the risk of harmful or misleading outputs, it is critical for these models to provide well-calibrated estimates of their confidence in completing a given task. This project aims to develop a methodology for evaluating the calibration of current foundation models and identifying areas where their self-assessments are most likely to fail.

Message To Sponsor

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