Chunhan Li — accepted AI-conference papers

2026

MGAL: A Multilingual Granularity-Aware Long-Context Benchmark

Chunhan Li, Chenglin Xu, Zongyang Zhang, Jiale Liu, Zhuoxi Rao, Xudong jia +5

ICML 2026poster

Evaluation of long-context Large Language Models (LLMs) has advanced rapidly. However, most existing benchmarks are limited to the document level and focus mainly on high-resource languages, leaving many fine-grained challenges insufficiently evaluated. To address this gap, we present MGAL, the firs…

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2026

Seizure-Semiology-Suite($S^3$): A Clinically Multimodal Dataset, Benchmark, and Models for Seizure Semiology Understanding

Lina Zhang, Jiarui Cui, Tonmoy Monsoor, Peizheng Li, Xinyi Peng, Chong Han +20

ICML 2026spotlight

While Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in general video understanding, their capacity to interpret involuntary, and spatio-temporally evolving pathologic motor behaviors such as seizure semiology remains largely untested. To address this gap, we intro…

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