Papers by Taihang Wang

1 papers
TAMA: Target-Aware Multilingual Abuse Detection by Cascaded Conditional Multi-Task Learning (2026.acl-long)

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Challenge: Existing models for protecting public figures from online abuse ignore who is targeted and how.
Approach: They propose a target-aware multi-task framework that conditions downstream predictions on upstream beliefs via three lightweight modules: Cross-Task Feature Fusion (CTF), Task-Adaptive Gating (TAG), and Label-Guided Span Detection (LGSD).
Outcome: The proposed framework yields higher average F1 than single-task training and standard multi-task learning.

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