Papers by Bill Howe

2 papers
Do Language Models Mirror Human Confidence? Exploring Psychological Insights to Address Overconfidence in LLMs (2025.findings-acl)

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Challenge: Psychology research has shown that humans are poor at estimating their performance on tasks, tending towards underconfidence on easy tasks and overconfidence on difficult tasks.
Approach: They propose to use a self-assessment method to assess confidence in large language models (LLMs) they propose to ask for the answer separately and then use them to improve their accuracy.
Outcome: The proposed method improves confidence calibration and interpretability in QA tasks with different personas.
Characterizing LLM Abstention Behavior in Science QA with Context Perturbations (2024.findings-emnlp)

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Challenge: Prior work has investigated the ability of LLMs to abstain from answering context-dependent questions when provided insufficient or inconsistent context is provided.
Approach: They propose to improve abstention when provided insufficient or incorrect context . they probed the ability of LLMs to abstain from answering context-dependent science questions .
Outcome: The proposed models abstain from answering science questions when provided insufficient or incorrect context.

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