Kyunghwan An — accepted AI-conference papers

2026

VinQA: Visual Elements Interleaved Long-form Answer Generation for Real-World Multimodal Document QA

Young Rok Jang, Hyesoo Kong, Kyunghwan An, Jae Sub Huh, Gyeonghun KIM, Stanley Jungkyu Choi

CVPR 2026

Real-world documents combine text with tables, charts, photographs, and diagrams arranged in diverse layouts, yet existing research on multimodal large language models (MLLMs) for document QA predominantly produces text-only responses, underutilizing these visual elements. We introduce VinQA, a data

Cited by 0 Source ↗Scholar ↗

2024

Structure-Aware Multimodal Sequential Learning for Visual Dialog

Young-Jin Kim, Min-Jun Kim, Kyunghwan An, Jinwoo Ahn, Jaeseok Kim, Yu-Jung Heo +2

AAAI 2024technical

With the ability to collect vast amounts of image and natural language data from the web, there has been a remarkable advancement in Large-scale Language Models (LLMs). This progress has led to the emergence of chatbots and dialogue systems capable of fluent conversations with humans. As the variety…

Cited by 1 Source ↗PDF ↗Scholar ↗