most citedRetrieval-augmented generation in multilingual settings

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2026

Inference-Free Multimodal Learned Sparse Retrieval for Production-Scale Visual Document Search

Gyu-Hwung Cho, Youngjune Lee, Kiyoon Jeong +5

As large-scale visual-document corpora such as arXiv papers and enterprise PDFs continue to grow, visual-document retrieval has gained increasing attention; yet it still lacks a de…

cs.CL2024

Context Embeddings for Efficient Answer Generation in RAG

David Rau, Shuai Wang, Hervé Déjean +1

Retrieval-Augmented Generation (RAG) allows overcoming the limited knowledge of LLMs by extending the input with external information. As a consequence, the contextual inputs to th…

cs.CL20242 cited

Retrieval-augmented generation in multilingual settings

Nadezhda Chirkova, David Rau, Hervé Déjean +3

Retrieval-augmented generation (RAG) has recently emerged as a promising solution for incorporating up-to-date or domain-specific knowledge into large language models (LLMs) and im…

cs.CL2024

BERGEN: A Benchmarking Library for Retrieval-Augmented Generation

David Rau, Hervé Déjean, Nadezhda Chirkova +4

Retrieval-Augmented Generation allows to enhance Large Language Models with external knowledge. In response to the recent popularity of generative LLMs, many RAG approaches have be…

cs.IR2024

SPLATE: Sparse Late Interaction Retrieval

Thibault Formal, Stéphane Clinchant, Hervé Déjean +1

The late interaction paradigm introduced with ColBERT stands out in the neural Information Retrieval space, offering a compelling effectiveness-efficiency trade-off across many ben…