CV

Education

M.S. in Computer Applied Technology, Peking University, 2021
- Document Analysis
- Table Detection & Recognition
B.S. in Computer Science & Technology, Peking University, 2018

Work experience

2021.7 - present: Algorithm Engineer @ Alibaba Group
- Model inference optimization in AI Earth team
- Neural Architecture Search, Object Detection, Quantization in TinyML team
- Data-Centric LLMs, Multimodal LLMs in SysML team

Publications

BOTS: A Unified Framework for Bayesian Online Task Selection in LLM Reinforcement Finetuning

Qianli Shen, Daoyuan Chen, Yilun Huang, Zhenqing Ling, Yaliang Li, Bolin Ding, Jingren Zhou. "BOTS: A Unified Framework for Bayesian Online Task Selection in LLM Reinforcement Finetuning." In The Fourteenth International Conference on Learning Representations. 2026.

Data-Juicer 2.0: Cloud-Scale Adaptive Data Processing for and with Foundation Models

Chen, Daoyuan*, Yilun Huang*, Xuchen Pan, Nana Jiang, Haibin Wang, Ce Ge, Yushuo Chen et al. "Data-Juicer 2.0: Cloud-Scale Adaptive Data Processing for and with Foundation Models." In The Thirty-ninth Annual Conference on Neural Information Processing Systems. 2025. Spotlight.

Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs

Fei Wei, Daoyuan Chen, Ce Wang, Yilun Huang, Yushuo Chen, Xuchen Pan, Yaliang Li, Bolin Ding. "Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs." arXiv preprint arXiv:2510.25441 (2025).

Trinity-RFT: A General-Purpose and Unified Framework for Reinforcement Fine-Tuning of Large Language Models

Pan, Xuchen, Yanxi Chen, Yushuo Chen, Yuchang Sun, Daoyuan Chen, Wenhao Zhang, Yuexiang Xie, Yilun Huang, Yilei Zhang, Dawei Gao, Yaliang Li, Bolin Ding, Jingren Zhou. "Trinity-RFT: A General-Purpose and Unified Framework for Reinforcement Fine-Tuning of Large Language Models." arXiv preprint arXiv:2505.17826 (2025).

DetailMaster: Can Your Text-to-Image Model Handle Long Prompts?

Jiao, Qirui, Daoyuan Chen, Yilun Huang, Xika Lin, Ying Shen, and Yaliang Li. "DetailMaster: Can Your Text-to-Image Model Handle Long Prompts?." arXiv preprint arXiv:2505.16915 (2025).

Img-Diff: Contrastive Data Synthesis for Multimodal Large Language Models

Jiao, Qirui, Daoyuan Chen, Yilun Huang, Bolin Ding, Yaliang Li, and Ying Shen. "Img-diff: Contrastive data synthesis for multimodal large language models." In Proceedings of the Computer Vision and Pattern Recognition Conference, pp. 9296-9307. 2025.

Data-Juicer Sandbox: A Comprehensive Suite for Multimodal Data-Model Co-development

Chen, Daoyuan*, Haibin Wang*, Yilun Huang*, Ce Ge, Yaliang Li, Bolin Ding, and Jingren Zhou. "Data-juicer sandbox: A feedback-driven suite for multimodal data-model co-development." In Forty-second International Conference on Machine Learning. 2025. Spotlight.

The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective

Qin, Zhen, Daoyuan Chen, Wenhao Zhang, Liuyi Yao, Yilun Huang, Bolin Ding, Yaliang Li, and Shuiguang Deng. "The synergy between data and multi-modal large language models: A survey from co-development perspective." IEEE Transactions on Pattern Analysis and Machine Intelligence (2025).

Enhancing Multimodal Large Language Models with Vision Detection Models: An Empirical Study

Jiao, Qirui, Daoyuan Chen, Yilun Huang, Yaliang Li, and Ying Shen. "Enhancing Multimodal Large Language Models with Vision Detection Models: An Empirical Study." arXiv preprint arXiv:2401.17981 (2024).

Data-Juicer: A One-Stop Data Processing System for Large Language Models

Chen, Daoyuan*, Yilun Huang*, Zhijian Ma*, Hesen Chen*, Xuchen Pan, Ce Ge, Dawei Gao et al. "Data-juicer: A one-stop data processing system for large language models." In Companion of the 2024 International Conference on Management of Data, pp. 120-134. 2024.

DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network

Shen, Xuan, Yaohua Wang, Ming Lin, Yilun Huang, Hao Tang, Xiuyu Sun, and Yanzhi Wang. "DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 6163-6173. 2023.

DAMO-YOLO : A Report on Real-Time Object Detection Design

Xu, Xianzhe*, Yiqi Jiang*, Weihua Chen*, Yilun Huang*, Yuan Zhang*, and Xiuyu Sun. "DAMO-YOLO: A Report on Real-Time Object Detection Design." arXiv preprint arXiv:2211.15444 (2022).

Rethinking table structure recognition using sequence labeling methods

Li, Yibo, Yilun Huang, Ziyi Zhu, Lemeng Pan, Yongshuai Huang, Lin Du, Zhi Tang, and Liangcai Gao. "Rethinking table structure recognition using sequence labeling methods." In International Conference on Document Analysis and Recognition, pp. 541-553. Springer, Cham, 2021.

NTable: A Dataset for Camera-Based Table Detection

Zhu, Ziyi, Liangcai Gao, Yibo Li, Yilun Huang, Lin Du, Ning Lu, and Xianfeng Wang. "NTable: A Dataset for Camera-Based Table Detection." In International Conference on Document Analysis and Recognition, pp. 117-129. Springer, Cham, 2021.

A YOLO-based table detection method

Huang, Yilun, Qinqin Yan, Yibo Li, Yifan Chen, Xiong Wang, Liangcai Gao, and Zhi Tang. "A YOLO-based table detection method." In 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 813-818. IEEE, 2019.

A GAN-based feature generator for table detection

Li, Yibo, Liangcai Gao, Zhi Tang, Qinqin Yan, and Yilun Huang. "A GAN-based feature generator for table detection." In 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 763-768. IEEE, 2019.

ICDAR 2019 Competition on Table Detection and Recognition (cTDaR)

Gao, Liangcai, Yilun Huang, Hervé Déjean, Jean-Luc Meunier, Qinqin Yan, Yu Fang, Florian Kleber, and Eva Lang. "ICDAR 2019 competition on table detection and recognition (cTDaR)." In 2019 International Conference on Document Analysis and Recognition (ICDAR), pp. 1510-1515. IEEE, 2019.