Paper#LLM, E-commerce, Live Streaming, Morph Detection, Data Augmentation🔬 ResearchAnalyzed: Jan 3, 2026 16:09
Chinese Morph Resolution in E-commerce Live Streaming
Analysis
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
“By leveraging large language models (LLMs) to generate additional training data, we improved performance and demonstrated that morph resolution significantly enhances live streaming regulation.”