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Byung Hyun Lee

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#artificial intelligence Preprint Oct 2026

Strong Helps Weak: Directional Cross-Modal Alignment Transfer in Multi-modal LLMs

Multi-modal large language models (MLLMs) achieve strong modality understanding by pairing a large language model (LLM) with an encoder for a target modality such as vision, video, or audio. However, improving an MLLM's capability for a given modality typically requires additional training on large modality-specific da...

H. Seo, Byung Hyun Lee, Minjun Kim et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Benchmarking Vision-Language Models for Automated Pathology Diagnosis and Report Generation

A clinically curated Pan-Asia WSI--report dataset is introduced and the REG 2025 benchmark is established as a benchmark for evaluating WSI-based structured report generation and vision-language understanding in computational pathology, providing insights for the design of clinically grounded multimodal pathology model...

Yu-Mi Lee, Harim Oh, Hyo-yun Kim et al. · 0 citations