Dense retrieval (DR) converts queries and documents into dense embeddings and
measures the similarity between queries and documents in vector space. One of the major …

This paper introduces PAG-a novel optimization and decoding approach that guides
autoregressive generation of document identifiers in generative retrieval models through …

Recent research has shown that transformer networks can be used as differentiable search
indexes by representing each document as a sequence of document ID tokens. These …

In today's digital age, accessing information across language barriers poses a significant
challenge, with conventional search systems often struggling to interpret and retrieve …

Multilingual information retrieval (MLIR) considers the problem of ranking documents in
several languages for a query expressed in a language that may differ from any of those …

Recent work in cross-language information retrieval (CLIR), where queries and documents
are in different languages, has shown the benefit of the Translate-Distill framework that …

The exclusion of monolingual natives from cyberspace is a global socioeconomic and
cultural problem. Efforts at addressing this problem have been socioeconomic, culminating …

Search engines play a crucial role in organizing and delivering information to billions of
users worldwide. However, these systems often reflect and amplify existing societal biases …

Information retrieval across different languages is an increasingly important challenge in
natural language processing. Recent approaches based on multilingual pre-trained …

In the contemporary digital landscape, search engines play an invaluable role in information
access, yet they often face challenges in Cross-Lingual Information Retrieval (CLIR) …