Papers with natural language matching

2 papers
WhiteningBERT: An Easy Unsupervised Sentence Embedding Approach (2021.findings-emnlp)

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Challenge: Pre-trained language models perform well on learning sentence semantics when fine-tuned with supervised data.
Approach: They conduct a thorough examination of pretrained model based unsupervised sentence embeddings.
Outcome: The proposed approach improves on whitening-based vector normalization with less than 10 lines of code.
Matching Article Pairs with Graphical Decomposition and Convolutions (P19-1)

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Challenge: Existing methods for matching sentence pairs do not perform well in longer documents . Existing approaches for matching sentences do not work in longer document understanding tasks .
Approach: They propose to model article pairs by comparing sentences that enclose same concept vertex . they propose to use a concept interaction graph to match articles by encoding sentences .
Outcome: The proposed methods show significant improvements over existing methods . the proposed datasets consist of 30K pairs of breaking news articles .

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