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 …

Large language models (LLMs) augmented with external data have demonstrated
remarkable capabilities in completing real-world tasks. Techniques for integrating external …

Retrieval-augmented generation (RAG) techniques have proven to be effective in integrating
up-to-date information, mitigating hallucinations, and enhancing response quality …

Latency and efficiency issues are often overlooked when evaluating IR models based on
Pretrained Language Models (PLMs) in reason of multiple hardware and software testing …

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 …

As information retrieval researchers, we not only develop algorithmic solutions to hard
problems, but we also insist on a proper, multifaceted evaluation of ideas. The literature on …

In the field of information retrieval, Query Likelihood Models (QLMs) rank documents based
on the probability of generating the query given the content of a document. Recently …

The Differentiable Search Index (DSI) is an emerging paradigm for information retrieval.
Unlike traditional retrieval architectures where index and retrieval are two different and …

This paper outlines a conceptual framework for understanding recent developments in
information retrieval and natural language processing that attempts to integrate dense and …

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