Papers with attentional neural networks

1 papers
Sparse, Dense, and Attentional Representations for Text Retrieval (2021.tacl-1)

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Challenge: Dual encoders perform retrieval by encoding documents and queries into dense low-dimensional vectors, scoring each document by its inner product with the query.
Approach: They propose a dual-encoder-based neural model that combines the efficiency of dual encoders with expressiveness of more costly attentional architectures.
Outcome: The proposed model outperforms strong alternatives in large-scale retrieval.

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