Papers by Maor Juliet Lavi

1 papers
Detecting (Un)answerability in Large Language Models with Linear Directions (2026.eacl-long)

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Challenge: Large language models (LLMs) often respond confidently to questions even when they lack the necessary information, leading to inaccurate responses or hallucinations.
Approach: They propose an approach for identifying a direction in the model’s activation space that captures unanswerability and uses it for classification.
Outcome: The proposed method detects unanswerable questions and generalizes better across datasets than existing prompt-based and classifier-based approaches.

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