2 papers
cs.CY2026
When VLMs 'Fix' Students: Identifying and Penalizing Over-Correction in the Evaluation of Multi-line Handwritten Math OCR
Jin Seong, Wencke Liermann, Minho Kim +2
Accurate transcription of handwritten mathematics is crucial for educational AI systems, yet current benchmarks fail to evaluate this capability properly. Most prior studies focus…
cs.CL2026
Do LLMs Need Inherent Reasoning Before Reinforcement Learning? A Study in Korean Self-Correction
Hongjin Kim, Jaewook Lee, Kiyoung Lee +3
Large Language Models (LLMs) demonstrate strong reasoning and self-correction abilities in high-resource languages like English, but their performance remains limited in low-resour…