Abstract
The AI era has ushered in Large Language Models (LLM) to the technological forefront, which has been much of the talk in 2023, and is likely to remain as such for many years to come. LLMs are the AI models that are the power house behind generative AI applications such as ChatGPT. These AI models, fueled by vast amounts of data and computational prowess, have unlocked remarkable capabilities, from human-like text generation to assisting with natural language understanding (NLU) tasks. They have quickly become the foundation upon which countless applications and software services are being built, or at least being augmented with. However, as with any groundbreaking innovations, the rise of LLMs brings forth critical safety, privacy, and ethical concerns. These models are found to have a propensity to leak private information, produce false information, and can be coerced into generating content that can be used for nefarious purposes by bad actors, or even by regular users unknowingly. Implementing safeguards and guardrailing techniques is imperative for applications to ensure that the content generated by LLMs are safe, secure, and ethical. Thus, frameworks to deploy mechanisms that prevent misuse of these models via application implementations is imperative. In this study, wepropose a Flexible Adaptive Sequencing mechanism with trust and safety modules, that can be used to implement safety guardrails for the development and deployment of LLMs.
Abstract (translated)
人工智能时代带来了大型语言模型（LLM）的技术前沿地位，这是2023年热议的话题，并且在未来几年内很可能继续保持这一趋势。这些大型语言模型是像ChatGPT这样的生成式AI应用背后的动力源泉。这些由海量数据和计算能力驱动的AI模型解锁了诸多令人惊叹的能力，从生成逼真的文本到协助处理自然语言理解（NLU）任务。它们已经迅速成为无数应用程序和服务的基础，或是被增强的基础。然而，如同任何突破性的创新一样，大型语言模型的崛起带来了重大的安全、隐私和伦理问题。这些模型被认为有泄露私人信息的趋势，会产生虚假信息，并可能在恶意行为者的操纵下生成用于不良目的的内容，甚至是在普通用户不知情的情况下。因此，为了确保由LLM生成的内容是安全、可靠且合乎道德规范的，必须实施防护措施和技术手段来限制这些模型被滥用的可能性。为此，在本研究中我们提出了一种带有信任和安全保障模块的灵活自适应序列机制，可用于在大型语言模型的发展和部署过程中实现安全性保障。
URL
https://arxiv.org/abs/2601.14298
