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Sunghwan Steve Cho

ACL 2026×2CVPR 2026多模态社会与人本可解释性评测与基准智能体与工具
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1 一作 · 3 篇 · ACL 2026 / CVPR 2026

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2026 顶会论文

3
一作ACL 2026Findings· Findings of ACL

MI - CXR : A Benchmark for Longitudinal Reasoning over Multi-Interval Chest X -rays

Sunghwan Steve Cho · Yunseok Han · Jaeyoung Do

摘要

Longitudinal chest X-ray (CXR) interpretation requires reasoning over disease evolution across multiple patient visits, yet most existing medical VQA benchmarks focus on single images or short-horizon image pairs. We introduce MI-CXR , a benchmark for standardized evaluation of M ulti- I nterval...

多模态可解释性评测与基准OpenReview 项目页
作者位次 #3/4ACL 2026Findings· Findings of ACL

MATA : Multi-Agent Framework for Reliable and Flexible Table Question Answering

Sieun Hyeon · Jusang Oh · Sunghwan Steve Cho · Jaeyoung Do

摘要

Recent advances in Large Language Models (LLMs) have significantly improved table understanding tasks such as Table Question Answering (TableQA), yet challenges remain in ensuring reliability, scalability, and efficiency, especially in resource-constrained or privacy-sensitive environments. In th...

智能体与工具效率与系统推理OpenReview 项目页

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