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Nour Jedidi

SIGIR 2026×2检索与知识可解释性评测与基准数据与预训练安全
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一作贡献30
核心/参与12
方向广度10
合作网络3
1 一作 · 2 篇 · SIGIR 2026

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2026 顶会论文

2
一作SIGIR 2026Poster· Information Retrieval (Short)

Revisiting BM25 Feedback Models using HyDE

Nour Jedidi · Jimmy Lin

摘要

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 when expanding queries for BM25. Instead, they often opt for a simple string concatenation of the query and LLM-genera...

检索与知识可解释性评测与基准OpenReview
作者位次 #2/3SIGIR 2026Poster· Information Retrieval (Resource)

NanoKnow: How to Know What Your Language Model Knows

Lingwei Gu · Nour Jedidi · Jimmy Lin

摘要

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 recent release of nanochat – a family of small LLMs with fully open pre-training data – addresses this as it provid...

数据与预训练检索与知识安全OpenReview

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