Papers by Yusong Tan

3 papers
BadWindtunnel: Defending Backdoor in High-noise Simulated Training with Confidence Variance (2025.findings-acl)

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Challenge: Current backdoor attack defenders in NLP typically involve data reduction or model pruning, risking losing crucial information.
Approach: They propose a backdoor defender that allows precise control over training conditions to model backdoor learning behavior without affecting the final model.
Outcome: The proposed model reduces the backdoor learning behavior without affecting the final model.
MixTEA: Semi-supervised Entity Alignment with Mixture Teaching (2023.findings-emnlp)

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Challenge: Existing methods to learn informative entity embeddings are insufficient for semi-supervised entity alignment.
Approach: They propose a semi-supervised method which guides the model learning with an end-to-end mixture teaching of manually labeled mappings and probabilistic pseudo mappings.
Outcome: The proposed method is superior to existing methods on benchmark datasets and further analyses.
Span-based Joint Entity and Relation Extraction with Attention-based Span-specific and Contextual Semantic Representations (2020.coling-main)

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Challenge: Existing methods treat each span token equally important, ignoring significant features.
Approach: They propose a span-based joint extraction framework with attention-based semantic representations that utilizes span-specific and contextual representations.
Outcome: The proposed model outperforms existing models on ACE2005, CoNLL2004 and ADE.

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