4 papers · 1 filter
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…
Revisiting Feedback Models for HyDE
Nour Jedidi, Jimmy Lin
Recent approaches that leverage large language models (LLMs) for pseudo-relevance feedback (PRF) have generally not utilized well-established feedback models like Rocchio and RM3 w…
Study on LLMs for Promptagator-Style Dense Retriever Training
Daniel Gwon, Nour Jedidi, Jimmy Lin
Promptagator demonstrated that Large Language Models (LLMs) with few-shot prompts can be used as task-specific query generators for fine-tuning domain-specialized dense retrieval m…
Don't "Overthink" Passage Reranking: Is Reasoning Truly Necessary?
Nour Jedidi, Yung-Sung Chuang, James Glass +1
With the growing success of reasoning models across complex natural language tasks, researchers in the Information Retrieval (IR) community have begun exploring how similar reasoni…