REC-CBM: Rubric-Aware Error-Correction Concept Bottleneck Models for Trustworthy Open-Ended Grading

ArXi:2605.27402v1 Announce Type: cross Open-ended grading is central to equitable and personalized education, yet manual grading remains time-consuming and costly, underscoring the need for automated grading systems. Although recent neural and large language model (LLM) based systems have nstrated superior performance, they are typically black-box models whose scoring processes and rationales are difficult for educators to verify and trust.