Papers by Gautier Izacard

2 papers
Task-aware Retrieval with Instructions (2023.findings-acl)

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Challenge: Existing models that learn intents from labeled data are complicated and require a vast number of annotated examples to train a model.
Approach: They propose a general-purpose task-aware retrieval system with instructions that can adapt to a new task without any parameter updates.
Outcome: The proposed system outperforms two benchmarks on a set of domains and tasks on X2-Retrieval.
Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering (2021.eacl-main)

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Challenge: Existing approaches to extracting answer from text are expensive to train and train.
Approach: They investigate how much models benefit from retrieving text passages . they obtain state-of-the-art results on the Natural Questions and TriviaQA open benchmarks ."
Outcome: The proposed model performs better when retrieving more passages than previously thought .

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