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Flower is a federated learning framework and distributed machine learning orchestrator designed to train models across decentralized devices. It functions as a privacy-preserving toolkit that enables model training and data analysis on local hardware, ensuring raw data remains on the device while contributing to a synchronized global model. The system employs an agnostic wrapper and integrator to connect diverse machine learning libraries, allowing different frameworks to operate within the same training loop. It uses a remote procedure call orchestrator to manage the exchange of model weight
PromptInject is a framework that assembles prompts in a modular fashion to provide a quantitative analysis of the robustness of LLMs to adversarial prompt attacks. 🏆 Best Paper Awards @ NeurIPS ML Safety Workshop 2022
In this paper, we conduct the first work to propose the concept of indirect jailbreak and achieve Retrieval-Augmented Generation (RAG) via LangChain. Building on this, we further design a novel method of indirect jailbreak attack, termed Poisoned-LangChain (PLC), which leverages a poisoned…
This is the official repo of the paper "Attack Prompt Generation for Red Teaming and Defending Large Language Models" accepted to Findings of EMNLP 2023.
A framework to evaluate the generalization capability of safety alignment for LLMs
The main features of robustnlp/cipherchat are: Jailbreak Attack Methods, Privacy and Safety.
Projects with overlapping indexed features include: adap/flower — Flower is a federated learning framework and distributed machine learning orchestrator designed to train models across… agencyenterprise/promptinject — PromptInject is a framework that assembles prompts in a modular fashion to provide a quantitative analysis of the… cam-fss/jailbreak-langchain — In this paper, we conduct the first work to propose the concept of indirect jailbreak and achieve Retrieval-Augmented… chawins/pal — Chawin Sitawarin 1 Norman Mu 1 David Wagner 1 Alexandre Araujo 2. confident-ai/deepteam. aatrox103/sap — This is the official repo of the paper "Attack Prompt Generation for Red Teaming and Defending Large Language Models"…