Paper summary
Paper summary: Absolute Zero: Reinforced Self-play Reasoning with Zero Data
Absolute Zero trains a model to propose its own coding and maths-style tasks and then solve them, with a code executor checking both, so reasoning improves through self-play with no external training data.
- The same model plays two roles: task proposer and solver.
- A code executor validates proposed tasks and verifies answers, which gives a reliable reward without human labels.