Papers by Sanzhar Umbet

1 papers
Confidence Under the Hood: An Investigation into the Confidence-Probability Alignment in Large Language Models (2024.acl-long)

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Challenge: Large Language Models (LLMs) are increasingly used in high-stakes areas such as healthcare, law, and education.
Approach: They propose a concept of Confidence-Probability Alignment that connects an LLM’s internal confidence to the confidence conveyed in the model’s response when explicitly asked about its certainty.
Outcome: The proposed model shows the strongest confidence-probability alignment across a wide range of tasks.

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