Papers by Stéphane Clinchant

2 papers
BERGEN: A Benchmarking Library for Retrieval-Augmented Generation (2024.findings-emnlp)

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Challenge: Retrieval-Augmented Generation allows to enhance Large Language Models with external knowledge.
Approach: They propose a library that allows to benchmark and standardize RAG experiments.
Outcome: The proposed library is an end-to-end library for reproducible research standardizing RAG experiments.
PISCO: Pretty Simple Compression for Retrieval-Augmented Generation (2025.findings-acl)

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Challenge: Document compression methods suffer from accuracy losses and limited context size.
Approach: They propose a method that achieves a 16x compression rate with minimal accuracy loss . they show that PISCO outperforms existing compression models by 8% in accuracy .
Outcome: The proposed method outperforms existing compression models by 8% in accuracy.

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