Papers by Hanpin Wang

2 papers
Beyond Single View: A Comprehensive Benchmark for Medical Multimodal Large Language Models on Multi-Image Understanding (2026.acl-long)

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Challenge: Existing benchmarks for multimodal large language models are limited to multiview diagnostics.
Approach: They propose a benchmark specifically designed for medical multi-image understanding that evaluates MLLMs across four dimensions.
Outcome: The proposed model performs better in multi-image contexts than open-source models . the model perform better when processing increased visual loads than closed-source ones .
MLeVLM: Improve Multi-level Progressive Capabilities based on Multimodal Large Language Model for Medical Visual Question Answering (2024.findings-acl)

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Challenge: Existing MVQA models ignore multi-level progressive capabilities due to unspecific data and plain architecture.
Approach: They propose a multi-level visual language model for medical visual question answering (MVQA) which covers multi- level questions and answers as well as reasoning processes from visual clues to semantic cognition.
Outcome: The proposed model outperforms existing medical multimodal large language models on a multi-level instruction dataset and a feature alignment module.

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