Papers with Multi-layer Representations

1 papers
Investigating Multi-layer Representations for Dense Passage Retrieval (2025.findings-emnlp)

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Challenge: Dense retrieval models adopt vectors from the last hidden layer of the document encoder to represent a document, which is in contrast to the fact that representations in different layers of a pre-trained language model contain different kinds of linguistic knowledge and behave differently during fine-tuning.
Approach: They propose to utilize representations from multiple encoder layers to make up the representation of a document, which they denote Multi-layer Representations (MLR).
Outcome: The proposed model outperforms dual encoder, ME-BERT and ColBERT in the single-vector retrieval setting and with other advanced training techniques.

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