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arXiv · 2610.05238

The Law of DeepSeek

Jyh-An Lee·Xuan Sun
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Abstract

Amid the intensifying competition in artificial intelligence between the United States and China, the emergence of the DeepSeek-R1 model has sent significant ripples through the technology sector, capital markets, and policy circles. This Article offers a comprehensive analysis of legal and policy landscape surrounding DeepSeek, drawing upon its key technical features-including reinforcement learning, mixture-experts architecture, multi-head latent attention mechanism, knowledge distillation, and open-source approach. Firstly, DeepSeek's success raises crtitical questions about the efficacy of the United States' increasingly robust export control measures on chips and semiconductors, components essential for training large language models. Secondly, akin to Chinese technology giants such as TikTok and Huawei, DeepSeek is confronted with information security scrutiny in the United States and other jurisdictions. Thirdly, despite its domain-specific capabilities and competitive API pricing, DeepSeek has faced criticism for producing outputs laden with political and ideological biases, igniting debates over free speech and censorship. Further more, this Article delves into intellectual property and contractual concerns stemming from the knowledge distillation technique employed by DeepSeek. Ultimately, it concludes that geopolitical consideration will continue to exert a profound influence on the legal challenges and prospective solutions related to the DeepSeek models.

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Jyh-An Lee, Xuan Sun. 2026-10-04. The Law of DeepSeek. https://arxiv.org/abs/2610.05238

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