[R] Identifying the Risks of LM Agents with an LM-Emulated Sandbox - University of Toronto 2023 - Benchmark consisting of 36 high-stakes tools and 144 test cases!

Paper: [https://arxiv.org/abs/2309.15817](https://arxiv.org/abs/2309.15817)

Github: [https://github.com/ryoungj/toolemu](https://github.com/ryoungj/toolemu)

Website: [https://toolemu.com/](https://toolemu.com/)

Abstract:

>Recent advances in Language Model (LM) agents and tool use, exemplified by applications like ChatGPT Plugins, enable a rich set of capabilities but also amplify potential risks - such as leaking private data or causing financial losses. Identifying these risks is labor-intensive, necessitating implementing the tools, manually setting up the environment for each test scenario, and finding risky cases. As tools and agents become more complex, the high cost of testing these agents …

abstract advances agents amplify applications capabilities cases chatgpt chatgpt plugins data environment financial labor language language model losses machinelearning plugins private data risks set test tool tools