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Chun-Fu Yeh

2 accepted papers

2024

AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model

EMNLP 2024industry

We present Any-Modality Augmented Language Model (AnyMAL), a unified model that reasons over diverse input modality signals (i.e. text, image, video, audio, IMU motion sensor), and generates textual responses. AnyMAL inherits the powerful text-based reasoning abilities of the state-of-the-art LLMs i…

2020

Self-similarity Student for Partial Label Histopathology Image Segmentation

ECCV 2020poster

Delineation of cancerous regions in gigapixel whole slide images (WSIs) is a crucial diagnostic procedure in digital pathology. This process is time-consuming because of the large search space in the gigapixel WSIs, causing chances of omission and misinterpretation at indistinct tumor lesions. To ta…

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