Papers by Yajun Du

2 papers
Penetrating Linguistic Disguises: A Slang-aware Label-Aligned Framework for Fine-Grained Toxicity Extraction in Chinese Hate Speech Detection (2026.findings-acl)

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Challenge: Flexible word boundaries and linguistic obfuscation, particularly slang, challenge precise span-level hate speech detection in Chinese.
Approach: They propose a Slang-aware Label-Aligned Framework that maps slang to explicit hate semantics and uses task-specific branches to mitigate feature interference.
Outcome: The proposed framework reduces ambiguity by mapping obscure slang to explicit hate semantics.
Mitigating Spurious Correlations in Text Classification Using Latent Space Geometry (2026.acl-long)

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Challenge: Existing models rely on predictive shortcuts that hold in training data but break under distribution shifts, leading to large performance drops for minority groups.
Approach: They propose a framework that transforms abstract biases into interpretable geometric anchors without auxiliary classifiers by manipulating latent space geometry.
Outcome: The proposed framework outperforms state-of-the-art baselines and improves worst-group accuracy by over 20% on the CivilComments dataset.

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