I am currently a second-year master’s student at Tsinghua Shenzhen International Graduate School, Tsinghua University, affiliated with the Intelligent Computing Lab. My supervisor is Prof. Xiu Li, and I have received a lot of research guidance from my senior fellow student Jiafei Lyu. My main research focus on Reinforcement Learning, especially on Agent Exploration, Multi-Agent Reinforcement Learning and RLHF of Large Models. I am proficient and interested in using mathematical theory to optimize reinforcement learning methods.

If you believe I am a good fit for your position, please don’t hesitate to contact me at yk22@mails.tsinghua.edu.cn.

News

• 2024.7 The papers “CMBE: Curiosity-driven Model-Based Exploration for Multi-Agent Reinforcement Learning in Sparse Reward Settings” and “Multi-agent Exploration with Sub-state Entropy Estimation” are accpepted by International Joint Conference on Neural Networks 2024.

• 2024.6 The paper “A two-stage reinforcement learning-based approach for multi-entity task allocation” is accepted by Engineering Applications of Artificial Intelligence.

• 2024.5 The paper “Exploration and Anti-Exploration with Distributional Random Network Distillation” is accepted by ICML 2024.

• 2024.4 The work “BATON: Aligning Text-to-Audio Model with Human Preference Feedback” is accepted by IJCAI 2024.

• 2024.2 The paper “Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model” is accepted by CVPR 2024.

• 2024.2 The work “BATON: Aligning Text-to-Audio Model with Human Preference Feedback” is on Arxiv.

• 2024.1 My work “Exploration and Anti-Exploration with Distributional Random Network Distillation” is on Arxiv.

• 2023.11 The paper “Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model” is selected as HuggingFace daily paper.

• 2023.11 My work “Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model” is on Arxiv.

Publications

• Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model. Kai Yang, Jian Tao, Jiafei Lyu, Chunjiang Ge, Jiaxin Chen, Weihan Shen, Xiaolong Zhu, Xiu Li. IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024. (Huggingface Daily Paper).
• Exploration and Anti-Exploration with Distributional Random Network Distillation. Kai Yang, Jian Tao, Jiafei Lyu, Xiu Li. International Conference on Machine Learning (ICML), 2024.
• BATON: Aligning Text-to-Audio Model with Human Preference Feedback. Huan Liao, Haonan Han, Kai Yang, Tianjiao Du, Rui Yang, Zunnan Xu, Qinmei Xu, Jingquan Liu, Jiasheng Lu, Xiu Li. International Joint Conference on Artificial Intelligence (IJCAI), 2024.
• A two-stage reinforcement learning-based approach for multi-entity task allocation. Aicheng Gong, Kai Yang, Jiafei Lyu, Xiu Li. Engineering Applications of Artificial Intelligence (EAAI) 136, 108906.
• GTLMA: Generalizable Hierarchical Learning for Tasks with Variable Entities. Kai Yang, Aicheng Gong, Jian Tao, Yang Zhang, Xiu Li. 2023 International Conference on Frontiers of Robotics and Software Engineering (FRSE).
• CMBE: Curiosity-driven Model-Based Exploration for Multi-Agent Reinforcement Learning in Sparse Reward Settings. Kai Yang, Zhirui Fang, Xiu Li, Jian Tao. 2024 International Joint Conference on Neural Networks (IJCNN), 1-8.
• Multi-agent Exploration with Sub-state Entropy Estimation. Jian Tao, Yangkun Chen, Yang Zhang, Kai Yang, Xiu Li. 2024 International Joint Conference on Neural Networks (IJCNN), 1-9.
• A novel ensemble approach for road traffic carbon emission prediction: a case in Canada. Yongliang Liu, Chunling Tang, Aiying Zhou, Kai Yang. Environment, Development and Sustainability.

Educations

2022-present: Pursuing Master’s Degree in Artificial Intelligence at Tsinghua Shenzhen International Graduate School, Tsinghua University.

2018-2022: Bachelor’s Degree in Automation from the Department of Electronic Information Engineering, Xi’an Jiaotong University.

Honors & Awards

2024.10: National Scholarship of Tsinghua University.

2023.10: First class scholarship of Tsinghua Shenzhen International Graduate School.

2022.10: Outstanding graduates of Xi’an Jiaotong University.

2021.10: School-level scholarship of Xi’an Jiaotong University.

2021.10: School-level outstanding student of Xi’an Jiaotong University.

2020.10: School-level scholarship of Xi’an Jiaotong University.

2020.10: School-level outstanding student of Xi’an Jiaotong University.

2019.10: School-level scholarship of Xi’an Jiaotong University.

2019.10: School-level outstanding student of Xi’an Jiaotong University.

Competitions

Math:

• First Prize in the National Finals of the 13th Chinese Mathematics Competitions (CMC), ranking 7th nationwide.

• third prize in the National Finals of the 3rd Hua Jiao Cup Mathematics Competition.

• Second Prize at the provincial level in the 12th Chinese Mathematics Competitions (CMC).

Computer Science:

• 1st place in the “Gorgewalk_v2” environment of the Tencent Honor of Kings AI Challenge.

• Top 20 in the “hok_1v1” environment of the Tencent Honor of Kings AI Challenge.

• Top 20 in the RLChina AI Challenge - RenYin Winter Season.

• Honorable Mention Award in the 2021 Mathematical Contest in Modeling (MCM).

Internships

Tencent TEG, Machine Learning Platform Department

Reseach on efficient RLHF-based fine-tuning methods for improving LLM performance.

Parametrix Technology Company

Research on how to enhance AIGC performance using RLHF and developing baseline algorithms code for the Kaggle Lux competition.

Teaching

Teaching Assistant of the course Introduction to Reinforcement Learning instructed by Prof. Xiu Li, Spring 2024.