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What does “on-policy” actually modify?
“On-policy” tells you where the training states came from. It does not tell you which way the KL points.
What does “on-policy” actually modify?
OPD-CORE-v1 · canonical teaching contract A student generates a response. A teacher is queried along that response. A KL loss compares their next-token distributions. Which part makes the recipe on-policy?
The answer is the first part: the student generated the response trajectory, so the response's prefixes are student-visited states. Forward KL, reverse KL, and other divergences describe a different choice—the local comparison made after a prefix has been selected.
Source-backed: Agarwal et al.'s GKD objective exposes a student-output fraction separately from the divergence choice. See the author manuscript §3.1 and §4 variants.
Write the source outside the local loss
Let name the source of prompt–response pairs. Once a response is sampled, its prefixes identify where teacher and student will be compared:
The expectation chooses trajectories and therefore visited prefixes. The inner compares two distributions at one already chosen prefix. In other words, prefix provenance and divergence direction are different decisions. Keeping those jobs on separate lines is the central habit of this guide.
Place the recipe on both coordinates
A fixed prompt set does not settle the source axis. GKD can sample prompts from a fixed collection and still sample completions from the current student. Conversely, a fixed teacher-generated completion can be paired with reverse KL without becoming on-policy.
The loss does not choose the prefix. So what does?