Papers by Jason Kuen
Learning Adaptive Axis Attentions in Fine-tuning: Beyond Fixed Sparse Attention Patterns (2022.findings-acl)
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Zihan Wang, Jiuxiang Gu, Jason Kuen, Handong Zhao, Vlad Morariu, Ruiyi Zhang, Ani Nenkova, Tong Sun, Jingbo Shang
| Challenge: | Adaptive Axis Attention learns different attention patterns for each task and model layer . sparse attention patterns do not improve the run time of the models but they reduce model memory requirements . |
| Approach: | They propose a method that learns different attention patterns for each Transformer layer . they propose 'adaptive axis attention' method that identifies important tokens . |
| Outcome: | The proposed method does not require pre-training to accommodate sparse attention patterns. |
A Critical Analysis of Document Out-of-Distribution Detection (2023.findings-emnlp)
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Jiuxiang Gu, Yifei Ming, Yi Zhou, Jason Kuen, Vlad Morariu, Handong Zhao, Ruiyi Zhang, Nikolaos Barmpalios, Anqi Liu, Yixuan Li, Tong Sun, Ani Nenkova
| Challenge: | Existing document understanding models focus on single-modal inputs such as images or texts. |
| Approach: | They propose to use a spatial-aware adapter to adapt transformer-based language models to document domain to exploit multi-modal information. |
| Outcome: | The proposed model significantly improves the OOD detection performance compared to using a standard language model and to competitive baselines. |