This paper provides an extensive and thorough overview of the models and techniques
utilized in the first and second stages of the typical information retrieval processing chain …

As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …

Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …

Recent years have witnessed a substantial increase in the use of deep learning to solve
various natural language processing (NLP) problems. Early deep learning models were …

PyTerrier is a Python-based retrieval framework for expressing simple and complex
information retrieval (IR) pipelines in a declarative manner. While making use of the long …

Pre-trained language models are increasingly important components across multiple
information retrieval (IR) paradigms. Late interaction, introduced with the ColBERT model …

Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have
shown the usefulness of expanding and reweighting the users' initial queries using …

Dense retrieval systems conduct first-stage retrieval using embedded representations and
simple similarity metrics to match a query to documents. Its effectiveness depends on …

The advent of transformer-based models such as BERT has led to the rise of neural ranking
models. These models have improved the effectiveness of retrieval systems well beyond that …

The Relevance Feedback (RF) process relies on accurate and real-time relevance
estimation of feedback documents to improve retrieval performance. Since collecting explicit …