Multi-step Jailbreaking Privacy Attacks on ChatGPT. (arXiv:2304.05197v1 [cs.CL])

With the rapid progress of large language models (LLMs), many downstream NLP
tasks can be well solved given good prompts. Though model developers and
researchers work hard on dialog safety to avoid generating harmful content from
LLMs, it is still challenging to steer AI-generated content (AIGC) for the
human good. As powerful LLMs are devouring existing text data from various
domains (e.g., GPT-3 is trained on 45TB texts), it is natural to doubt whether
the private information is included in …

attacks chatgpt data developers dialog domains generated gpt gpt-3 hard human information jailbreaking language language models large llms nlp privacy progress prompts rapid researchers safety text threats training work