Papers by Zhibin Xiao

2 papers
Empowering Backbone Models for Visual Text Generation with Input Granularity Control and Glyph-Aware Training (2024.emnlp-main)

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Challenge: Existing text-to-image models struggle to generate images with legible visual texts . current models lack support for Chinese texts, misspelling, and lack of diversity .
Approach: They propose to empower backbone models to generate visual texts in Chinese and English . they propose to augment conventional training objective with glyph-aware training losses .
Outcome: The proposed methods can generate visual texts in English and Chinese while maintaining image generation quality.
Rethinking Network Pruning – under the Pre-train and Fine-tune Paradigm (2021.naacl-main)

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Challenge: Existing pruning results on benchmark transformers, such as BERT, are not as remarkable as those of convolutional neural networks.
Approach: They propose to apply a knowledge-aware pruning process to transformer-based pre-trained language models to reduce model size and model weight.
Outcome: The proposed pruning method outperforms the leading competitors with a 20-times weight/FLOPs compression and neglectable loss in prediction accuracy.

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