Papers by Dae Yon Hwang

2 papers
Link, Synthesize, Retrieve: Universal Document Linking for Zero-Shot Information Retrieval (2024.emnlp-main)

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Challenge: Existing methods for zero-shot learning are sparse, but have been used for dense retrieval (DR) .
Approach: They propose a novel Universal Document Linking algorithm which links similar documents to enhance synthetic query generation across multiple datasets with different characteristics.
Outcome: The proposed algorithm surpasses state-of-the-art methods in zero-shot cases.
EmbedTextNet: Dimension Reduction with Weighted Reconstruction and Correlation Losses for Efficient Text Embedding (2023.findings-acl)

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Challenge: EmbedTextNet is a light add-on network that can be appended to an arbitrary language model to generate a compact embedding without requiring any changes in its architecture or training procedure.
Approach: They propose an add-on network that can be appended to an arbitrary language model to generate a compact embedding without requiring any changes in its architecture or training procedure.
Outcome: The proposed network can be appended to an arbitrary language model to generate a compact embedding without any changes in its architecture or training procedure.

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