New Energy‑Based Interpreter Reveals Prompt Sentences Driving Black‑Box LLMs
The authors train an Energy‑Based Model to mimic a proprietary LLM’s internal representations, then use a lightweight network to attribute a target output to specific prompt sentences. Crucially, the interpreter works after a single surrogate training phase and requires no further API calls, opening a path to responsible auditing of closed‑source LLMs.