Papers by Shunsuke Kitada

3 papers
AraDIC: Arabic Document Classification Using Image-Based Character Embeddings and Class-Balanced Loss (2020.acl-srw)

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Challenge: a novel image-based character embedding framework is used for text classification in Arabic . classical methods require morphological analysis, word segmentation, and hand-crafted feature engineering.
Approach: They propose a novel end-to-end Arabic document classification framework, Arabic document image-based classifier, inspired by image-basic character embeddings.
Outcome: The proposed framework improves on modern standard Arabic, colloquial Arabic, and Classical Arabic.
A11y-Compressor: A Framework for Enhancing the Efficiency of GUI Agent Observations through Visual Context Reconstruction and Redundancy Reduction (2026.acl-srw)

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Challenge: Existing approaches to grounding GUI environments are categorized into image-based and text-based representations.
Approach: They propose a framework that transforms linearized accessibility trees into compact and structured representations.
Outcome: The proposed framework reduces input tokens to 22% of the original while improving task success rates by 5.1 percentage points on average.
Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation (2020.aacl-srw)

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Challenge: a character-based text classification framework for non-alphabetic languages is proposed . glyphs are used to give visual meaning to characters, such as "" and "."
Approach: They propose a character-based text classification framework for non-alphabetic languages . they propose glyph-aware disentangled character embeddings that are dimensionally independent .
Outcome: The proposed framework improves the performance of Japanese text classification tasks . it provides embedding interpretability and performance competitively with the state-of-the-art model .

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