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Liat Ein-Dor

ACL 2026×2NeurIPS 2026评测与基准检索与知识智能体与工具推理可解释性
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0 一作 · 3 篇 · ACL 2026 / NeurIPS 2026

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2026 顶会论文

3
作者位次 #5/5ACL 2026Poster· Natural Language Processing

Masked by Consensus: Disentangling Privileged Knowledge in LLM Correctness

Tomer Ashuach · Shai Gretz · Yoav Katz · Yonatan Belinkov · Liat Ein-Dor

摘要

Humans use introspection to evaluate their understanding through private internal states inaccessible to external observers. We investigate whether large language models possess similar privileged knowledge about answer correctness, information unavailable through external observation. We train c...

检索与知识推理可解释性OpenReview 项目页
作者位次 #4/5ACL 2026Findings· Findings of ACL

Fine-Grained Detection of Context-Grounded Hallucinations Using LLM s

Yehonatan Peisakhovsky · Zorik Gekhman · Yosi Mass · Liat Ein-Dor · Roi Reichart

摘要

Context-grounded hallucinations are cases where model outputs contain information not verifiable against the source text. We study the applicability of LLMs for localizing such hallucinations, as a more practical alternative to existing complex evaluation pipelines. In the absence of established...

评测与基准检索与知识对齐与偏好OpenReview 项目页

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