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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.23280 |
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| _version_ | 1866911343220621312 |
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| author | Zhu, Jiahao Qiang, Jipeng Bai, Ran Liu, Chenyu Ouyang, Xiaoye |
| author_facet | Zhu, Jiahao Qiang, Jipeng Bai, Ran Liu, Chenyu Ouyang, Xiaoye |
| contents | E-commerce live streaming in China, particularly on platforms like Douyin, has become a major sales channel, but hosts often use morphs to evade scrutiny and engage in false advertising. This study introduces the Live Auditory Morph Resolution (LiveAMR) task to detect such violations. Unlike previous morph research focused on text-based evasion in social media and underground industries, LiveAMR targets pronunciation-based evasion in health and medical live streams. We constructed the first LiveAMR dataset with 86,790 samples and developed a method to transform the task into a text-to-text generation problem. By leveraging large language models (LLMs) to generate additional training data, we improved performance and demonstrated that morph resolution significantly enhances live streaming regulation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_23280 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Chinese Morph Resolution in E-commerce Live Streaming Scenarios Zhu, Jiahao Qiang, Jipeng Bai, Ran Liu, Chenyu Ouyang, Xiaoye Computation and Language E-commerce live streaming in China, particularly on platforms like Douyin, has become a major sales channel, but hosts often use morphs to evade scrutiny and engage in false advertising. This study introduces the Live Auditory Morph Resolution (LiveAMR) task to detect such violations. Unlike previous morph research focused on text-based evasion in social media and underground industries, LiveAMR targets pronunciation-based evasion in health and medical live streams. We constructed the first LiveAMR dataset with 86,790 samples and developed a method to transform the task into a text-to-text generation problem. By leveraging large language models (LLMs) to generate additional training data, we improved performance and demonstrated that morph resolution significantly enhances live streaming regulation. |
| title | Chinese Morph Resolution in E-commerce Live Streaming Scenarios |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2512.23280 |