Papers by Parishad BehnamGhader

2 papers
Exploiting Instruction-Following Retrievers for Malicious Information Retrieval (2025.findings-acl)

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Challenge: Instruction-following retrievers are increasingly used in real-world applications, but little research has investigated the safety risks associated with their increasing search capabilities.
Approach: They investigate the ability of retrievers to satisfy malicious queries . they find that for >50% of queries, retrievers can select harmful passages .
Outcome: The findings highlight the safety risks associated with instruction-following retrievers . they show that even safety-aligned LLMs can satisfy malicious requests .
Can Retriever-Augmented Language Models Reason? The Blame Game Between the Retriever and the Language Model (2023.findings-emnlp)

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Challenge: kNN-LM, REALM, DPR + FiD, Contriever + ATLAS, and Contriver + Flan-T5 are popular retriever-augmented language models for a variety of tasks.
Approach: They evaluate the strengths and weaknesses of kNN-LM, REALM, DPR + FiD, Contriever + ATLAS, and Contriver + Flan-T5 in reasoning over retrieved statements across different tasks.
Outcome: The proposed models do not exhibit strong reasoning even when provided with only the required statements.

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