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 …

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 …

The core of information retrieval (IR) is to identify relevant information from large-scale
resources and return it as a ranked list to respond to user's information need. In recent years …

Knowledge-intensive language tasks (KILT) usually require a large body of information to
provide correct answers. A popular paradigm to solve this problem is to combine a search …

Recent advances in Information Retrieval utilise energy-intensive hardware to produce state-
of-the-art results. In areas of research highly related to Information Retrieval, such as Natural …

Knowledge-intensive language tasks (KILTs) benefit from retrieving high-quality relevant
contexts from large external knowledge corpora. Learning task-specific retrievers that return …

The recent advent of end-to-end generative retrieval marks a significant shift in document
retrieval methods, leveraging differentiable search indexes to directly produce relevant …

Generative information retrieval, encompassing two major tasks of Generative Document
Retrieval (GDR) and Grounded Answer Generation (GAR), has gained significant attention …

Model-based Information Retrieval (Model-based IR) has gained attention due to
advancements in generative language models. Unlike traditional dense retrieval methods …

Recent advances in large language models have enabled the development of viable
generative retrieval systems. Instead of a traditional document ranking, generative retrieval …