RubricWorld: World Model-Guided Rubric Optimization for LLM Graders
Rubric optimization improves LLM grading by revising scoring instructions while keeping the grader's parameters fixed. Existing optimizers often judge edits by aggregate validation performance, limiting the supervision they retain about which errors an edit corrects or introduces. Testing each candidate also requires rescoring validation answers, which limits how many edits can be explored within…
We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.
