Cross-Platform Chinese Offensive Comment Detection via Dual-Threshold Hard Example Mining
Cross-platform deployment of offensive comment detection for Chinese social media suffers performance degradation. The paper proposes a dual-threshold hard mining method to address this. First, the clean-Chinese-base RoBERTa is finetuned on COLD to establish a binary baseline for fair comparison. Second, a three-class fine-labeled test set covering Weibo, Xiaohongshu, Tieba, and Zhihu is constructed, domain distances from the source are quantified using Jaccard and Proxy-A Distance, as well as the degradation bottleneck of the baseline under domain shift is systematically revealed. Herein, a dual threshold hard example mining strategy is proposed. High- and low-confidence error-prone samp...
| Authors | Ruixing Ren, Junhui Zhao, Fangfang Wang |
|---|---|
| Primary category | cs.CL |
| Published | 26 June 2026 |
| Last updated at source | 26 June 2026 |
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