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Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive Translators
Published in EMNLP, 2022
Xinyou Wang*, Zaixiang Zheng, and Shujian Huang
Keywords: non-autoregressive generation, neural machine translation, multi-task learning
Recommended citation: Xinyou Wang*, Zaixiang Zheng, and Shujian Huang. (2022). "Helping the Weak Makes You Strong: Simple Multi-Task Learning Improves Non-Autoregressive Translators." Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 5513-5519.
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Diffusion Language Models Are Versatile Protein Learners
Published in ICML, 2024
Xinyou Wang*, Zaixiang Zheng*, Fei Ye, Dongyu Xue, Shujian Huang, and Quanquan Gu
Keywords: diffusion protein language models, protein sequence generation, protein representation learning, controllable protein design
Recommended citation: Xinyou Wang*, Zaixiang Zheng*, Fei Ye, Dongyu Xue, Shujian Huang, and Quanquan Gu. (2024). "Diffusion Language Models Are Versatile Protein Learners." Proceedings of the 41st International Conference on Machine Learning, 52309-52333.
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DPLM-2: A Multimodal Diffusion Protein Language Model
Published in ICLR, 2025
Xinyou Wang*, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, and Quanquan Gu
Keywords: multimodal protein language models, discrete diffusion, structure tokenization, sequence-structure co-generation
Recommended citation: Xinyou Wang*, Zaixiang Zheng, Fei Ye, Dongyu Xue, Shujian Huang, and Quanquan Gu. (2025). "DPLM-2: A Multimodal Diffusion Protein Language Model." International Conference on Learning Representations.
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ProteinBench: A Holistic Evaluation of Protein Foundation Models
Published in ICLR, 2025
Fei Ye, Zaixiang Zheng, Dongyu Xue, Yuning Shen, Lihao Wang, Yiming Ma, Yan Wang, Xinyou Wang, Xiangxin Zhou, and Quanquan Gu
Keywords: protein foundation models, holistic evaluation
Recommended citation: Fei Ye, Zaixiang Zheng, Dongyu Xue, Yuning Shen, Lihao Wang, Yiming Ma, Yan Wang, Xinyou Wang, Xiangxin Zhou, and Quanquan Gu. (2025). "ProteinBench: A Holistic Evaluation of Protein Foundation Models." International Conference on Learning Representations.
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Elucidating the Design Space of Multimodal Protein Language Models
Published in ICML, 2025
Xinyou Wang*, Cheng-Yen Hsieh*, Daiheng Zhang, Dongyu Xue, Fei Ye, Shujian Huang, Zaixiang Zheng, and Quanquan Gu
Keywords: multimodal protein language models, structure tokenization, geometric representation learning, protein folding
Recommended citation: Xinyou Wang*, Cheng-Yen Hsieh*, Daiheng Zhang, Dongyu Xue, Fei Ye, Shujian Huang, Zaixiang Zheng, and Quanquan Gu. (2025). "Elucidating the Design Space of Multimodal Protein Language Models." Proceedings of the 42nd International Conference on Machine Learning, 24156-24175.
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AITIME ICML 2025 Paper Preview: Elucidating the Design Space of Multimodal Protein Language Models
Published:
Presented “Elucidating the Design Space of Multimodal Protein Language Models” (ICML 2025 Spotlight).
