Papers by Chenlu Wang

2 papers
Paying Attention to Deflections: Mining Pragmatic Nuances for Whataboutism Detection in Online Discourse (2024.findings-acl)

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Challenge: Existing studies on whataboutism have focused on tracking "what about" phrases, but they neglect the unique challenges to its detection.
Approach: They propose to use attention weights to distinguish the ‘what about’ lexical construct from whataboutism by using Twitter/X and YouTube datasets.
Outcome: The proposed method improves by 4% and 10% over previous state-of-the-art methods in Twitter and YouTube datasets.
Class Distillation with Mahalanobis Contrast: An Efficient Training Paradigm for Pragmatic Language Understanding Tasks (2025.acl-long)

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Challenge: Existing classifiers for detecting deviant language often come with significant computational cost and high data demands.
Approach: They propose a class-disstillation paradigm that targets the core challenge: distilling a small, well-defined target class from a heterogeneous background.
Outcome: The proposed training paradigm outperforms baselines and large language models on three benchmarks.

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