Large Language Models (LLMs)
Our research in Large Language Models (LLMs) explores new frontiers in natural language understanding and generation. We focus on developing advanced models that push the limits of what AI can achieve in processing human language—enabling more accurate, efficient, and dynamic interactions.
Our Research on LLMs
Check Out Our Latest Research
FuzzAgent: AI Agent for Cybersecurity
FuzzAgent is an LLM-based cybersecurity agent designed to automate Prompt Injection attacks, using advanced capabilities to tackle complex security challenges. By specifying the target level on the gandalf site, FuzzAgent autonomously navigates through increasing difficulty, solving Level 7 in under 30 minutes—far surpassing typical human limitations. As a cutting-edge solution for LLM security, FuzzAgent highlights the power of combining human expertise with LLM-driven automation.
Agent O (Village): Multi-Agent
Agent O is an advanced LLM-based Multi-Agent solution designed to tackle complex problems that require specialized expertise. Unlike single-agent systems, Agent O utilizes multiple agents working together to deliver more accurate and efficient results. By leveraging deep knowledge in fields such as medicine and engineering, Agent O provides tailored, high-quality solutions to customer queries.
EVAL: Implementing Your Requests
EVAL is an autonomous AI agent developed to perform tasks based on simple user requests. By providing the desired outcome, EVAL independently searches the web, writes code, runs tests, and returns the result, even creating its own tools when needed. As the world’s first autonomous agent for web app development, EVAL has gained significant attention, including over 200,000 views on X.com (formerly Twitter).
