business enterprise
Finance Agents Got Rubrics With Values Frozen to a Cutoff
Expert guidance governed a writer, reviewer and code checks that generated task-specific scoring criteria.
Summary
Expert guidance governed a writer, reviewer and code checks that generated task-specific scoring criteria.
FinAutoRubric turns reusable expert guidance into query-specific rubrics for financial research agents. A writer researches expected values, a reviewer checks them, code enforces rules and unresolved failures escalate to a human. Across three expert-authored finance benchmarks, the authors report scoring agreement comparable with their strongest generator and a blind analyst preference for the generated rubrics. The released benchmark covers 100 queries across 78 tasks and eight asset classes; it evaluates rubric production, not investment performance.
Why it matters
Expert guidance governed a writer, reviewer and code checks that generated task-specific scoring criteria.
Limits and context
- The released benchmark covers 100 queries across 78 tasks and eight asset classes; it evaluates rubric production, not investment performance.
Key claims
Expert guidance governed a writer, reviewer and code checks that generated task-specific scoring criteria.
Qualification: The released benchmark covers 100 queries across 78 tasks and eight asset classes; it evaluates rubric production, not investment performance.
Evidence: source-2026-09-29-006
Sources
- arXiv preprint 2609.35744arXiv · primary research
Corrections
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