About Me

I am currently a Research Scientist at ByteDance (since April 2022), specializing in Large Language Model (LLM) Alignment and multimodal modeling within the Seed Team. Before this, I completed my Ph.D. at the Natural Language Processing Group of Nanjing University, co-supervised by Prof. Shujian Huang and Prof. Jiajun Chen. During my doctoral studies, I interned at ByteDance AI Lab under the mentorship of Prof. Zhou Hao and Prof. Lei Li.

My work bridges multiple areas:

• Generative Modeling: Autoregressive and Non-autoregressive frameworks (e.g., diffusion models)
• Structure-Aware: Graph-based representations (e.g., molecules), tree-structure (syntax tree), and sequential data (plain text) modeling
• Multimodality: Natural Language Sequence and Syntax, 1D-2D-3D Molecule, Audio-Text, etc.

We’re hiring! The ByteDance Seed Team is actively seeking exceptional talents in LLM. Feel free to contact me and apply via baoyu.001@bytedance.com for the Top Seed Internship program.

Selected Publications/Preprints [Full list]

[name*: equal contributions] [name: interns/students I mentored]

1. Shimao Zhang, Yu Bao, Shujian Huang, EDT: Improving Large Language Models by Entropy-based Dynamic Temperature Sampling, Preprint 2024.
2. Xiwei Cheng*, Xiangxin Zhou*, Yuwei Yang, Yu Bao, Quanquan GU, Decomposed direct preference optimization for structure-based drug design, Preprint 2024.
3. Xiangxin Zhou*, Xiwei Cheng*, Yuwei Yang, Yu Bao, Liang Wang, Quanquan Gu, DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization, ICLR 2024.
4. Jiaqi Guan*, Xiangxin Zhou*, Yuwei Yang, Yu Bao, Jian Peng, Jianzhu Ma, Qiang Liu, Liang Wang, Quanquan Gu, DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design, ICML 2023.
5. Min Liu, Yu Bao, Chengqi Zhao, Shujian Huang, Selective Knowledge Distillation for Non-Autoregressive Neural Machine Translation, AAAI 2023.
6. Yu Bao, Hao Zhou, Shujian Huang, Dongqi Wang, Lihua Qian, Xinyu Dai, Jiajun Chen, Lei Li, latent-GLAT: Glancing at Latent Variables for Parallel Text Generation, ACL 2022.
7. Yu Bao, Shujian Huang, Tong Xiao, Dongqi Wang, Xinyu Dai, Jiajun Chen, Non-Autoregressive Translation by Learning Target Categorical Codes, NAACL-HLT 2021.
8. Jiahuan Li*, Yu Bao*, Shujian Huang, Xinyu Dai, Jiajun Chen, Explicit Semantic Decomposition for Definition Generation, ACL 2020.
9. Yu Bao, Hao Zhou, Jiangtao Feng, Mingxuan Wang, Shujian Huang, Jiajun Chen, Lei Li, PNAT: Non-Autoregressive Transformer by Position Learning, Preprint 2019.
10. Yu Bao*, Hao Zhou*, Shujian Huang, Lei Li, Lili Mou, Olga Vechtomova, Xinyu Dai, Jiajun Chen, Generating Sentences from Disentangled Syntactic and Semantic Spaces, ACL 2019.

Professional Services

Area Chair of

• ACL Rolling Review 2025-
• The 1st GenBio Workshop on New Frontiers of Generative AI and Biology at NeurIPS 2023

Journal Reviewer of

• IEEE Transaction on Pattern Analysis and Machine Intelligence (TPAMI)
• IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
• Journal of Artificial Intelligence Research (JAIR)

PC Member/Reviewer of

• International Conference on Machine Learning (ICML) 2023-
• Annual Conference on Neural Information Processing Systems (NeurIPS) 2022-
• International Conference on Learning Representations(ICLR) 2022-
• North American Chapter of the Association for Computational Linguistics (NAACL) 2022-
• ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) 2022-
• AAAI Conference on Artificial Intelligence (AAAI) 2022-
• Annual Meeting of the Association for Computational Linguistics (ACL) 2021-
• Conference on Empirical Methods in Natural Language Processing (EMNLP) 2021-
• The Chinese National Conference on Computational Linguistics (CCL) 2022
• The CCF Conference on Natural Language Processing and Chinese Computing (NLPCC) 2022
• International Joint Conferences on Artificial Intelligence (IJCAI) 2020

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