specific method · filed under post-training
Deterministic chain of checkers
Applies deterministic reward checks in order, with the first failed check determining the reward.
- source
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- model
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- lab adopt it
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- strongest
- core
How sources treat it
One count per evidence span, weakest treatment to strongest.
core 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
Rewards are produced by a deterministic chain of checkers applied to every terminated rollout in the following order, with the first failing check determining the reward.
corepost trainingin Laguna XS.2Poolside
Filed alongside
Other methods under post-training :: reward modelling.
Generative Reward ModelGroupwise Agentic GradingGroupwise Reward SynthesisAdversarial screeningLength-adjusted RL rewardVerifier cross-checkingAbstention-aware reward for factual QAAgentic Generative Reward ModelBehavior rubricsBinary task verifierBinary terminal-verifier rewardCollaboration bonusDirect RL optimization of a generative reward modelFive-dimension comparative grading of passing patchesHack-agent screeningHybrid reward systemLanguage consistency rewardMonitoring-only penalty strategyMulti-level reward formulationMultiplicative reward synthesisNegative checks for unintended side effectsOutcome Reward ModelPer-token tool-error reward shapingPrinciple-conditioned Generative Reward Model