P-BERT: Toward Long Sequence Modeling by Enabling Language Representation With Prefix Sequence Compression, Soft Position Embedding, and Data Augmentation for Patent Relevance Assessment

Recent works have increasingly adopted pre-trained language models, such as BERT, to model technical semantics for patent relevance assessment. However, existing truncation and divide-merge strategies, used to handle input length constraints, results in feature loss and semantic isolation. This limi...

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Váldodahkkit:	Fei Wang, Xingchen Shi, Dongsheng Wang, Yinxia Lou
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	IEEE 2025-01-01
Ráidu:	IEEE Access
Fáttát:	Prefix sequence compression soft position embedding data augmentation patent relevance assessment
Liŋkkat:	https://ieeexplore.ieee.org/document/10902370/
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