Combining verifiable rewards with rubrics for more efficient model grading
stochasticchasm · x · 2026-09-22
- The thread discusses combining verifiable rewards with rubrics during model training: verifiable signals filter candidates, while synthesized rubrics differentially grade the outputs.
- The original poster describes an offline pipeline — synthesize rubrics, grade, then refine — and notes many extension paths: making each grading step agentic, running more refinement loops, etc.
- The reply suggests adding programming-style rubrics to differentiate further, and remarks that this puts the scale of grading compute into perspective.
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