Papers with Llama2Vec

1 papers
Llama2Vec: Unsupervised Adaptation of Large Language Models for Dense Retrieval (2024.acl-long)

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Challenge: Dense retrieval requires discriminative embeddings to represent the semantic relationship between query and document.
Approach: They propose an unsupervised approach that performs unsupervised adaptation of large language models for dense retrieval.
Outcome: The proposed model improves on a variety of dense retrieval benchmarks and is available on github.

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