# Lecture Notes on Neural Information Retrieval

arXiv: https://arxiv.org/abs/2207.13443 · HTML: https://mlsanity.com/paper/2207.13443/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jul 2022.

## Built on by (most cited first, 7 of 7)

- [Black-box Adversarial Attacks against Dense Retrieval Models: A Multi-view Contrastive Learning Method](https://mlsanity.com/paper/2308.09861/) (2023)
- [FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation](https://mlsanity.com/paper/2402.11891/) (2024)
- [Understanding and Mitigating the Threat of Vec2Text to Dense Retrieval Systems](https://mlsanity.com/paper/2402.12784/) (2024)
- [The Infinite Index: Information Retrieval on Generative Text-To-Image Models](https://mlsanity.com/paper/2212.07476/) (2022)
- [Telco-DPR: A Hybrid Dataset for Evaluating Retrieval Models of 3GPP Technical Specifications](https://mlsanity.com/paper/2410.19790/) (2024)
- [Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge Acquisition](https://mlsanity.com/paper/2505.07166/) (2025)
- [Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection](https://mlsanity.com/paper/2309.06131/) (2023)

## Abstract (arXiv)

These lecture notes focus on the recent advancements in neural information retrieval, with particular emphasis on the systems and models exploiting transformer networks. These networks, originally proposed by Google in 2017, have seen a large success in many natural language processing and information retrieval tasks. While there are many fantastic textbook on information retrieval and natural language processing as well as specialised books for a more advanced audience, these lecture notes target people aiming at developing a basic understanding of the main information retrieval techniques and approaches based on deep learning. These notes have been prepared for a IR graduate course of the MSc program in Artificial Intelligence and Data Engineering at the University of Pisa, Italy.