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cs.IR2026
Effective Dense Retrieval using Only In-Context Examples
Nour Jedidi, Abdul Basit Ali, Hang Li +1
Turning decoder-only large language models (LLMs) into strong dense retrievers typically requires some form of retriever training. In this paper, we ask whether LLMs can instead be…
cs.IR2026
A Systematic Study of Pseudo-Relevance Feedback with LLMs
Nour Jedidi, Jimmy Lin
Pseudo-relevance feedback (PRF) methods built on large language models (LLMs) can be organized along two key design dimensions: the feedback source, which is where the feedback tex…
cs.CL2026
NanoKnow: How to Know What Your Language Model Knows
Lingwei Gu, Nour Jedidi, Jimmy Lin
How do large language models (LLMs) know what they know? Answering this question has been difficult because pre-training data is often a "black box" - unknown or inaccessible. The…