Advanced Reinforcement Learning Interview Questions, issue 4, Jan 30, 2026
The LLM-as-a-Judge Trap
Machine Learning Engineer interview at DeepSeek, and the interviewer asks:
βWe want to train a reasoning model using ππ’π«πππ ππ«ππππ«ππ§ππ ππ©ππ’π¦π’π³πππ’π¨π§ (πππ), but we have zero budget for human annotators. How do we procedurally generate high-quality ππͺπ―π―π¦π³ π·π΄. ππ°π΄π¦π³ pairs from the modelβs own generations?β
Outsourcing preference labels to a stronger model just distills its bias, while execution-verified self-play produces cleaner gradients and scales without a teacher ceiling.
The full answer, with the mechanism and the arithmetic, is for paid subscribers on Substack.