TPN: Transferable Proto-Learning Network towards Few-shot Document-Level Relation Extraction

• URL: http://arxiv.org/abs/2410.00412v1
• Date: Tue, 1 Oct 2024 05:37:31 GMT
• Title: TPN: Transferable Proto-Learning Network towards Few-shot Document-Level Relation Extraction
• Authors: Yu Zhang, Zhao Kang,
• Abstract summary: Few-shot document-level relation extraction suffers from poor performance due to cross-domain transferability of NOTA relation representation. We introduce a Transferable Proto-Learning Network (TPN) to address the challenging issue. TPN comprises three core components: Hybrid hierarchically encodes semantic content of input text combined with attention information to enhance the relation representations.
• Score: 9.4094500796859
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Few-shot document-level relation extraction suffers from poor performance due to the challenging cross-domain transferability of NOTA (none-of-the-above) relation representation. In this paper, we introduce a Transferable Proto-Learning Network (TPN) to address the challenging issue. It comprises three core components: Hybrid Encoder hierarchically encodes semantic content of input text combined with attention information to enhance the relation representations. As a plug-and-play module for Out-of-Domain (OOD) Detection, Transferable Proto-Learner computes NOTA prototype through an adaptive learnable block, effectively mitigating NOTA bias across various domains. Dynamic Weighting Calibrator detects relation-specific classification confidence, serving as dynamic weights to calibrate the NOTA-dominant loss function. Finally, to bolster the model's cross-domain performance, we complement it with virtual adversarial training (VAT). We conduct extensive experimental analyses on FREDo and ReFREDo, demonstrating the superiority of TPN. Compared to state-of-the-art methods, our approach achieves competitive performance with approximately half the parameter size. Data and code are available at https://github.com/EchoDreamer/TPN.

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