Papers by Oren Glickman

2 papers
NER Retriever: Zero-Shot Named Entity Retrieval with Type-Aware Embeddings (2025.findings-emnlp)

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Challenge: NER Retriever uses a user-defined type description to retrieve documents mentioning entities of that type.
Approach: They propose a zero-shot retrieval framework for ad-hoc Named Entity Recognition . a user-defined type description is used to retrieve documents mentioning entities of that type .
Outcome: The proposed framework outperforms lexical and dense retrieval baselines on three benchmarks.
User-Centric Evidence Ranking for Attribution and Fact Verification (2026.eacl-long)

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Challenge: Large language models often present users with insufficient or redundant information, leading to inefficient and error-prone verification.
Approach: They propose a task that prioritizes presenting sufficient information as early as possible in a ranked list.
Outcome: The proposed task minimizes user reading effort while making all available evidence accessible for sequential verification.

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