Papers by Ziyi Kou
Domain Adaptation for Question Answering via Question Classification (2022.coling-1)
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| Challenge: | Question answering systems often experience performance deterioration upon user-generated questions. |
| Approach: | They propose a question classification framework to help QA domains adapt to different domains. |
| Outcome: | The proposed framework improves on state-of-the-art datasets against multiple datasets. |
RAt: Injecting Implicit Bias for Text-To-Image Prompt Refinement Models (2024.emnlp-main)
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| Challenge: | Text-to-image prompt refinement (T2I-Refine) aims to rephrase or extend an input prompt with more descriptive details that can be leveraged to generate images with higher quality. |
| Approach: | They develop an adversarial prompt attacking framework that implicitly attacks input prompts with intentional adversarials to generate images with higher quality. |
| Outcome: | The proposed framework can implicitly attack input prompts with implicit concept biases to generate images with higher quality and explicit visual bias towards the target group. |