# Evaluating Quantized Llama 2 Models for IoT Privacy Policy Language Generation
## 2 Related Work
### Privacy Policy of IoT Devices
\begin{table}
\begin{tabular}{c c c c} \hline
**Reference** & **Year** & **Title** & **Remarks** \\ \hline
[76] & 2017 & A survey of wearable devices and challenges & Reviews the usage of wearable devices, their functions and challenges, and the future trends. \\ \hline
[77] & 2017 & Future of IoT networks: A survey & Provides an in-depth analysis of IoT networks and their future developments. \\ \hline
[64] & 2017 & Toward an Approach to Privacy Notices in IoT & Reviews a method to extract notice and choice statements from privacy policies for IoT users to decide about their privacy. \\ \hline
[78] & 2018 & Privacy issues and solutions for consumer wearables & Provides a detailed explanation about the privacy issues of consumer wearables. \\ \hline
[79] & 2018 & Internet of Things (IoT): Research, Simulators, and Testbeds & Provides a comparative analysis of IoT simulators and test beds. \\ \hline
[65] & 2018 & Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning & Proposes an automated framework designed to analyze privacy policies (Polisis) using deep learning. \\ \hline
[66] & 2018 & Claudette Meets GDPR: Automating the Evaluation of Privacy Policies Using Artificial Intelligence & Presents a study on automating the legal evaluation of privacy policies under GDPR using AI. \\ \hline
[13] & 2018 & Large-scale readability analysis of privacy policies & Introduces an automated toolset for extracting and analyzing the readability of nearly 50,000 privacy policies. \\ \hline
[67] & 2018 & PrivOnto: A semantic framework for the analysis of privacy policies & Presents a framework to simplify the analysis of privacy policies using crowd sourcing, machine learning, and natural language processing. \\ \hline
[68] & 2019 & Demystifying IoT security: An exhaustive survey on IoT vulnerabilities and a first empirical look on Internet-scale IoT exploitations & Reviews vulnerabilities and suggests solutions and improvements for Internet of Things. \\ \hline
[80] & 2020 & A comprehensive overview of smart wearables: The state-of-art literature, recent advances, and future challenges & Reviews the works regarding current research trends, advancements, and future challenges of wearables between 2010 and 2019. \\ \hline
[81] & 2020 & Wearables and the Internet of Things (IoT), applications, opportunities, and challenges: A Survey & Reviews the current research challenges and issues within four different sectors: health, sports, tracking, and localization and safety. \\ \hline
[69] & 2021 & Automated Extraction and Presentation of Data Practices in Privacy Policies & Presents an automated tool called PI-Extract, which is designed specifically for privacy policy analysis using neural networks to extract personal data-handling practices from the privacy policies and represent the information more concisely. \\ \hline
[82] & 2021 & Recent Advances in Wearable Sensing Technologies & Presents the recent advancements in sensor technology and in wearables. \\ \hline
[83] & 2021 & A survey on wearable technology: History, state-of-the-art and current challenges & Provides a comprehensive historical review of wearable devices. Reports on applications and some aspects of security and privacy. \\ \hline
[70] & 2021 & AI-Based Analysis of Policies and Images for Privacy-Conscious Content Sharing & Reviews techniques aimed at assisting the user in taking privacy choices using machine learning, computer vision, and natural language processing techniques. \\ \hline \end{tabular}
\end{table} 
Table 2: _Cont._In this work, we evaluate 4-bit, 5-bit, and 8-bit quantized versions of the Llama 2 [25] (which is referred to as Bloke, available from Hugging Face [84]) and base Llama 2 models. The purpose of using quantized large language models (LLMs) over regular large language models (LLMs) is motivated by the fact that the quantized LLMs do not require powerful servers (thereby decreasing energy consumption [53]) and the use of data centers at the core of the Internet.