About me

Hi! I'm a fourth-year Ph.D. student at the Electrical and Computer Engineering Department of Carnegie Mellon University. I am fortunate to be advised by Prof. Yuejie Chi and Prof. Andrea Zanette. Previously I spent one year at Peking University for a data science master’s program. Before that, I received my B.S. in Mathematics (Honors Program) from Xi'an Jiaotong University. Here is my CV.

Research Interests

I'm interested in optimization and algorithm design in machine learning, with a focus spanning deep learning, reinforcement learning, game theory and more. Specifically, I’m enthusiastic about developing sample- and computationally efficient algorithms for large-scale ML problems.

Work Experience

• Machine Learning Student Researcher at Google Research (May 2025–Dec 2025)
• Machine Learning Student Researcher at Meta FAIR (May 2026–Current)

Selected Publications

• Stochastic Inertial Krasnosel’skii–Mann Iteration Achieves Near-Optimal Sample Complexity
  Preprint, 2026
  Tong Yang, Tao Jiang, Yuejie Chi, Ashok Cutkosky, Lin Xiao
  [PDF] [BibTex] @misc{yang2026stochasticinertialkrasnoselskiimanniteration, title={Stochastic Inertial Krasnosel'skii-Mann Iteration Achieves Near-Optimal Sample Complexity}, author={Tong Yang and Tao Jiang and Yuejie Chi and Ashok Cutkosky and Lin Xiao}, year={2026}, eprint={2609.28543}, archivePrefix={arXiv}, primaryClass={stat.ML}, url={https://arxiv.org/abs/2609.28543}, }

• Agentic Transformers Provably Learn to Search via Reinforcement Learning
  Preprint, 2026
  Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi
  [PDF] [BibTex] @article{yang2026agentic, title={Agentic Transformers Provably Learn to Search via Reinforcement Learning}, author={Yang, Tong and Huang, Yu and Liang, Yingbin and Chi, Yuejie}, journal={arXiv preprint arXiv:2606.00183}, year={2026} }

• Diffusion Controller: Framework, Algorithms and Parameterization
  ICML 2026
  Tong Yang, Moonkyung Ryu, Chih-Wei Hsu, Guy Tennenholtz, Yuejie Chi, Craig Boutilier, Bo Dai
  [PDF] [BibTex] @article{yang2026diffusion, title={Diffusion Controller: Framework, Algorithms and Parameterization}, author={Yang, Tong and Ryu, Moonkyung and Hsu, Chih-Wei and Tennenholtz, Guy and Chi, Yuejie and Boutilier, Craig and Dai, Bo}, journal={arXiv preprint arXiv:2603.06981}, year={2026} }

• Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL
  NeurIPS 2025
  Tong Yang, Bo Dai, Lin Xiao, Yuejie Chi
  [PDF] [BibTex] @article{yang2025exploration, title={Exploration from a Primal-Dual Lens: Value-Incentivized Actor-Critic Methods for Sample-Efficient Online RL}, author={Yang, Tong and Dai, Bo and Xiao, Lin and Chi, Yuejie}, journal={arXiv preprint arXiv:2506.22401}, year={2025} }

• Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent
  NeurIPS 2025
  Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi
  [PDF] [BibTex] @article{yang2025multi, title={Multi-head transformers provably learn symbolic multi-step reasoning via gradient descent}, author={Yang, Tong and Huang, Yu and Liang, Yingbin and Chi, Yuejie}, journal={arXiv preprint arXiv:2508.08222}, year={2025} }

• Incentivize without Bonus: Provably Efficient Model-based Online Multi-agent RL for Markov Games
  ICML 2025
  Tong Yang, Bo Dai, Lin Xiao, Yuejie Chi
  [PDF] [BibTex] @article{yang2025incentivize, title={Incentivize without bonus: Provably efficient model-based online multi-agent RL for Markov games}, author={Yang, Tong and Dai, Bo and Xiao, Lin and Chi, Yuejie}, journal={arXiv preprint arXiv:2502.09780}, year={2025} }

• Faster WIND: Accelerating Iterative Best-of-N Distillation for LLM Alignment
  AISTATS 2025
  Tong Yang, Jincheng Mei, Hanjun Dai, Zixin Wen, Shicong Cen, Dale Schuurmans, Yuejie Chi, Bo Dai
  [PDF] [BibTex] @article{yang2024faster, title={Faster WIND: Accelerating Iterative Best-of-$ N $ Distillation for LLM Alignment}, author={Yang, Tong and Mei, Jincheng and Dai, Hanjun and Wen, Zixin and Cen, Shicong and Schuurmans, Dale and Chi, Yuejie and Dai, Bo}, journal={arXiv preprint arXiv:2410.20727}, year={2024} }

• In-Context Learning with Representations: Contextual Generalization of Trained Transformers
  NeurIPS 2024
  Tong Yang, Yu Huang, Yingbin Liang, Yuejie Chi
  [PDF] [BibTex] @article{yang2024context, title={In-context learning with representations: Contextual generalization of trained transformers}, author={Yang, Tong and Huang, Yu and Liang, Yingbin and Chi, Yuejie}, journal={arXiv preprint arXiv:2408.10147}, year={2024} }

• Federated Natural Policy Gradient and Actor Critic Methods for Multi-task Reinforcement Learning
  NeurIPS 2024
  Tong Yang, Shicong Cen, Yuting Wei, Yuxin Chen, Yuejie Chi
  [PDF] [BibTex] @article{yang2023federated, title={Federated natural policy gradient methods for multi-task reinforcement learning}, author={Yang, Tong and Cen, Shicong and Wei, Yuting and Chen, Yuxin and Chi, Yuejie}, journal={arXiv preprint arXiv:2311.00201}, year={2023} }

• A Primal-Dual Approach to Solving Variational Inequalities with General Constraints
  ICLR 2024
  Tatjana Chavdarova*, Tong Yang*, Matteo Pagliardini, Michael I. Jordan (*equal contribution, order is alphabetical.)
  [PDF] [Poster (OPT@NeurIPS '22)] [BibTex] @article{chavdarova2022acvi, title = {Revisiting the ACVI Method for Constrained Variational Inequalities}, author = {Chavdarova, Tatjana and Pagliardini, Matteo and Yang, Tong and Jordan, Michael I.}, journal= {ArXiv:2210.15659}, year = {2022}, }

• Solving Constrained Variational Inequalities via an Interior Point Method
  ICLR 2023 Spotlight!
  Tong Yang*, Michael I. Jrodan*, Tatjana Chavdarova* (*equal contribution)
  [PDF] [Poster (WiML@ICML '22)] [Code] [BibTex] @article{yang2022acvi, title = {Solving Constrained Variational Inequalities via an Interior Point Method}, author = {Tong Yang and Michael I. Jordan and Tatjana Chavdarova}, journal = {ArXiv:2206.10575}, year = {2022}, }

• Optimization for Amortized Inverse Problems
  ICML 2023
  Tianci Liu*, Tong Yang*, Quan Zhang, Qi Lei (*equal contribution)
  [PDF] [BibTex] @inproceedings{liu2023optimization, title={Optimization for amortized inverse problems}, author={Liu, Tianci and Yang, Tong and Zhang, Quan and Lei, Qi}, booktitle={International Conference on Machine Learning}, pages={22289--22319}, year={2023}, organization={PMLR} }

• Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF
  ICLR 2025
  Shicong Cen, Jincheng Mei, Katayoon Goshvadi, Hanjun Dai, Tong Yang, Sherry Yang, Dale Schuurmans, Yuejie Chi, Bo Dai
  [PDF] [BibTex] @article{cen2024value, title={Value-Incentivized Preference Optimization: A Unified Approach to Online and Offline RLHF}, author={Cen, Shicong and Mei, Jincheng and Goshvadi, Katayoon and Dai, Hanjun and Yang, Tong and Yang, Sherry and Schuurmans, Dale and Chi, Yuejie and Dai, Bo}, journal={arXiv preprint arXiv:2405.19320}, year={2024} }