Papers by Amin Beheshti
VITAL: A New Dataset for Benchmarking Pluralistic Alignment in Healthcare (2025.acl-long)
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| Challenge: | Existing approaches to align Large Language Models with human values model an averaged or monolithic preference, despite progress in pluralistic alignment, no prior work has focused on health . |
| Approach: | They propose a benchmark dataset to assess and benchmark pluralistic alignment methodologies. |
| Outcome: | The proposed model can model pluralistic views within health domains. |
StyleDubber: Towards Multi-Scale Style Learning for Movie Dubbing (2024.findings-acl)
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Gaoxiang Cong, Yuankai Qi, Liang Li, Amin Beheshti, Zhedong Zhang, Anton Hengel, Ming-Hsuan Yang, Chenggang Yan, Qingming Huang
| Challenge: | Existing methods for movie dubbing break phonemes in scripts, resulting in incomplete phoneme pronunciation and poor identity stability. |
| Approach: | They propose a method that switches dubbing learning from frame level to phoneme level . it uses a multimodal style adaptor to learn pronunciation style from audio . |
| Outcome: | The proposed method improves on two benchmarks, V2C and Grid, and is available on github. |