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Tae-Ho Kim

2 accepted papers

2026

ERGO: Efficient High-Resolution Visual Understanding for Vision-Language Models

ICLR 2026poster

Efficient processing of high-resolution images is crucial for real-world vision–language applications. However, existing Large Vision-Language Models (LVLMs) incur substantial computational overhead due to the large number of vision tokens. With the advent of "thinking with images" models, reasoning…

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2020

Emotional Voice Conversion Using Multitask Learning with Text-To-Speech

ICASSP 2020accepted

Voice conversion (VC) is a task that alters the voice of a person to suit different styles while conserving the linguistic content. Previous state-of-the-art technology used in VC was based on the sequence-to-sequence (seq2seq) model, which could lose linguistic information. There was an attempt to…

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