Chinese Morph Resolution in E-commerce Live Streaming
Paper#LLM, E-commerce, Live Streaming, Morph Detection, Data Augmentation🔬 Research|Analyzed: Jan 3, 2026 16:09•
Published: Dec 29, 2025 08:04
•1 min read
•ArXivAnalysis
This paper addresses a practical problem in a rapidly growing market (e-commerce live streaming in China) by introducing a novel task (LiveAMR) and dataset. It leverages LLMs for data augmentation, demonstrating a potential solution for regulatory challenges related to deceptive practices in live streaming, specifically focusing on pronunciation-based morphs in health and medical contexts. The focus on a real-world application and the use of LLMs for data generation are key strengths.
Key Takeaways
- •Introduces the LiveAMR task for detecting pronunciation-based morphs in e-commerce live streaming.
- •Constructs a novel dataset with 86,790 samples.
- •Transforms the task into a text-to-text generation problem using LLMs.
- •Demonstrates improved performance through LLM-based data augmentation.
- •Highlights the potential of morph resolution for enhancing live streaming regulation.
Reference / Citation
View Original"By leveraging large language models (LLMs) to generate additional training data, we improved performance and demonstrated that morph resolution significantly enhances live streaming regulation."