Papers by Camille Couturier

1 papers
Hybrid-RACA: Hybrid Retrieval-Augmented Composition Assistance for Real-time Text Prediction (2024.emnlp-industry)

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Challenge: Large language models (LLMs) enhanced with retrieval augmentation have shown great performance in many applications, but their computational overhead and additional retrieval step limit their effectiveness in real-time tasks.
Approach: They propose a system that combines a cloud-based LLM with a smaller client-side model through retrieval augmented memory to provide real-time text prediction.
Outcome: The proposed system can generate better responses from the cloud-based model while maintaining low latency.

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