I am a second year PhD student in the David R. Cheriton School of Computer Science at the University of Waterloo, where I am fortunate to work under the supervision of Professor Jimmy Lin .

My research focuses on understanding how large language models can improve information access systems, studying the use of large language models across all aspects of the retrieval pipeline. I am generally interested in how large language models can be used to make information retrieval systems more effective, especially in settings where large-scale training data is unavailable. I also serve as an organizer of the TREC Retrieval-Augmented Generation (RAG) Track.

Previously, I graduated with a Master's degree from the Language Technologies Institute at Carnegie Mellon University, where I was advised by Professor Jamie Callan and Professor Eduard Hovy. After earning my Master's, I worked for two years as a researcher at MIT Lincoln Laboratory before starting my PhD.

Publications

1. Don't "Overthink" Pointwise Reranking: Is Reasoning Truly Necessary?
   Nour Jedidi, Yung-Sung Chuang, James Glass, and Jimmy Lin
   EMNLP Findings 2026
   
2. Project Greenhouse: Progress Toward Fully Open and Sovereign Agentic Search
   Jimmy Lin, Sahel Sharifymoghaddam, Lingwei Gu, and Nour Jedidi
   arXiv 2026
   
3. Effective Dense Retrieval using Only In-Context Examples
   Nour Jedidi, Abdul Basit Ali, Hang Li, and Jimmy Lin
   arXiv 2026
   
4. Revisiting BM25 Feedback Models using HyDE
   Nour Jedidi and Jimmy Lin
   SIGIR 2026
   
5. NanoKnow: How to Know What Your Language Model Knows
   Lingwei Gu^*, Nour Jedidi^*, and Jimmy Lin (^* equal contribution)
   SIGIR 2026
   
6. A Systematic Study of Pseudo-Relevance Feedback with LLMs
   Nour Jedidi and Jimmy Lin
   arXiv 2026
   
7. Study on LLMs for Promptagator-Style Dense Retriever Training
   Daniel Gwon^*, Nour Jedidi^*, and Jimmy Lin (^* equal contribution)
   CIKM 2025
   
8. From Reviews to Actionable Insights: An LLM-Based Approach for Attribute and Feature Extraction
   Khaled Boughanmi, Kamel Jedidi, and Nour Jedidi
   arXiv 2025
   
9. Choosing ‘Right’ from Wrong: A Closer Look at Selection Bias in Spatial Multiple-Choice Questions in Large Multimodal Models
   Giselle Zeno, Nour Jedidi, and Steven R. Gomez
   Benchmarking and Expanding AI Multimodal Approaches (BEAM) Workshop @ CVPR 2025
   ★ Best Paper Award
10. Zero-Shot Dense Retrieval with Embeddings from Relevance Feedback
    Nour Jedidi, Yung-Sung Chuang, Leslie Shing, and James Glass
    arXiv 2024