Papers with PGen
Scaling Back-Translation with Domain Text Generation for Sign Language Gloss Translation (2023.eacl-main)
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| Challenge: | Sign language gloss translation aims to translate the sign glosses into spoken language texts, which is challenging due to the scarcity of labeled gloss-text parallel data. |
| Approach: | They propose a back translation technique that generates pseudo-parallel data by translating in-domain spoken language texts into sign glosses. |
| Outcome: | The proposed method outperforms the BT methods on three benchmarks of sign language gloss translation in different languages. |
Personalized Generation In Large Model Era: A Survey (2025.acl-long)
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Yiyan Xu, Jinghao Zhang, Alireza Salemi, Xinting Hu, Wenjie Wang, Fuli Feng, Hamed Zamani, Xiangnan He, Tat-Seng Chua
| Challenge: | Recent advances in large generative models have catalyzed a paradigm shift in content generation to Personalized Generation (PGen). |
| Approach: | They propose a multi-level taxonomy that systematically formalizes PGen's key components, core objectives, and abstract workflows. |
| Outcome: | The proposed taxonomy bridging PGen research across multiple modalities highlights open challenges and promising directions for future exploration. |