Daekyung Park

Domain-specific agent evaluation no longer requires manual ground-truth curation: autonomous research and verification loops constrained by reusable expert rules yield grading rubrics that professional analysts prefer over expert baselines.

This work proposes a two-agent framework that first identifies the firms for which each alternative data channel is likely to be informative and then predicts revenue using firm- and channel-specific context and evaluates the framework across four commercial alternative data channels.