Papers by Hyunmin Song

2 papers
VEHME: A Vision-Language Model For Evaluating Handwritten Mathematics Expressions (2025.emnlp-main)

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Challenge: VEHME is a vision language model for assessing handwritten math answers . traditional methods of assessing student work are limited by time constraints, class sizes and cognitive load .
Approach: They propose a Vision-Language Model for Evaluating Handwritten Mathematics Expressions to assess handwritten math responses with high accuracy and interpretable reasoning traces.
Outcome: VEHME achieves state-of-the-art performance among open-source models and approaches accuracy of proprietary systems.
RingFormer: Rethinking Recurrent Transformer with Adaptive Level Signals (2025.findings-emnlp)

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Challenge: Transformers have shown strong performance in processing sequential data, but their parameters are larger . a novel approach to reduce the model parameters while maintaining high performance is proposed .
Approach: They propose a transformer-based model that processes input repeatedly in a circular, ring-like manner.
Outcome: The proposed approach reduces model parameters while maintaining high performance . the proposed approach is validated in the experiments.

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