Yuandong Tian

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 161

Top Venues

Publications

Zihan Ding, Amy Zhang, Yuandong Tian, Qinqing Zheng
Diffusion World Model. CoRR (2024)
Jian Xie, Kai Zhang, Jiangjie Chen, Tinghui Zhu, Renze Lou, Yuandong Tian, Yanghua Xiao, Yu Su
TravelPlanner: A Benchmark for Real-World Planning with Language Agents. CoRR (2024)
Yang Zhong, Weiping Dou, Andrew Cohen, Dia'a Bisharat, Yuandong Tian, Jiang Zhu, Qing Huo Liu
Image Classifier Based Generative Method for Planar Antenna Design. CoRR (2024)
Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian
SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems. ICML (2023)
Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. ICML (2023)
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen
O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. CoRR (2023)
Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Pengtao Xie, Hugh Leather, Yuandong Tian
Learning to compile smartly for program size reduction. CoRR (2023)
Danqing Wang, Kevin Yang, Hanlin Zhu, Xiaomeng Yang, Andrew Cohen, Lei Li, Yuandong Tian
Learning Personalized Story Evaluation. CoRR (2023)
Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu
Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. CoRR (2023)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. CoRR (2023)
Yuandong Tian, Yiping Wang, Zhenyu Zhang, Beidi Chen, Simon S. Du
JoMA: Demystifying Multilayer Transformers via JOint Dynamics of MLP and Attention. CoRR (2023)
Yuandong Tian, Yiping Wang, Beidi Chen, Simon S. Du
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer. CoRR (2023)
Yihao Zhao, Xiaoxiang Zhang, Hang Zhu, Ying Zhang, Zhaodong Wang, Yuandong Tian, Alex Nikulkov, Joao Ferreira, Xuanzhe Liu, Xin Jin
Klotski: Efficient and Safe Network Migration of Large Production Datacenters. SIGCOMM (2023)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Local Branching Relaxation Heuristics for Integer Linear Programs. CPAIOR (2023)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. ICML (2023)
Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian
Efficient Planning in a Compact Latent Action Space. ICLR (2023)
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, Mike Lewis
Efficient Streaming Language Models with Attention Sinks. CoRR (2023)
Shouyuan Chen, Sherman Wong, Liangjian Chen, Yuandong Tian
Extending Context Window of Large Language Models via Positional Interpolation. CoRR (2023)
Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. NeurIPS (2023)
Jiaxun Cui, Xiaomeng Yang, Mulong Luo, Geunbae Lee, Peter Stone, Hsien-Hsin S. Lee, Benjamin Lee, G. Edward Suh, Wenjie Xiong, Yuandong Tian
MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection. ICLR (2023)
Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum
A Cookbook of Self-Supervised Learning. CoRR (2023)
Arman Zharmagambetov, Brandon Amos, Aaron M. Ferber, Taoan Huang, Bistra Dilkina, Yuandong Tian
Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. CoRR (2023)
Yuandong Tian
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning. ICLR (2023)
Kevin Yang, Dan Klein, Nanyun Peng, Yuandong Tian
DOC: Improving Long Story Coherence With Detailed Outline Control. ACL (1) (2023)
Kevin Yang, Dan Klein, Asli Celikyilmaz, Nanyun Peng, Yuandong Tian
RLCD: Reinforcement Learning from Contrast Distillation for Language Model Alignment. CoRR (2023)
Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Chun-cheng Jason Chen, Mehrdad Mahdavi
DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. SDM (2023)
Hanlin Zhu, Andrew Cohen, Danqing Wang, Kevin Yang, Xiaomeng Yang, Jiantao Jiao, Yuandong Tian
End-to-end Story Plot Generator. CoRR (2023)
Andrew Cohen, Weiping Dou, Jiang Zhu, Slawomir Koziel, Peter Renner, Jan-Ove Mattsson, Xiaomeng Yang, Beidi Chen, Kevin Stone, Yuandong Tian
Modeling Scattering Coefficients using Self-Attentive Complex Polynomials with Image-based Representation. CoRR (2023)
Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Ré, Beidi Chen
Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. CoRR (2023)
Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh James Leather, Yuandong Tian
Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. ICML (2023)
Zhengyao Jiang, Yingchen Xu, Nolan Wagener, Yicheng Luo, Michael Janner, Edward Grefenstette, Tim Rocktäschel, Yuandong Tian
H-GAP: Humanoid Control with a Generalist Planner. CoRR (2023)
Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh
AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks. HPCA (2023)
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark W. Barrett, Zhangyang Wang, Beidi Chen
H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. NeurIPS (2023)
Yuandong Tian, Yiping Wang, Beidi Chen, Simon S. Du
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer. NeurIPS (2023)
Aaron M. Ferber, Arman Zharmagambetov, Taoan Huang, Bistra Dilkina, Yuandong Tian
GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature. CoRR (2023)
Kevin Yang, Yuandong Tian, Nanyun Peng, Dan Klein
Re3: Generating Longer Stories With Recursive Reprompting and Revision. EMNLP (2022)
Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR (2022)
Yulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du
Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games. AISTATS (2022)
Zhengyao Jiang, Tianjun Zhang, Michael Janner, Yueying Li, Tim Rocktäschel, Edward Grefenstette, Yuandong Tian
Efficient Planning in a Compact Latent Action Space. CoRR (2022)
Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen
On the Importance of Asymmetry for Siamese Representation Learning. CVPR (2022)
Chengyue Gong, Dilin Wang, Meng Li, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra
NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. ICLR (2022)
Tongzhou Wang, Simon S. Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian
Denoised MDPs: Learning World Models Better Than the World Itself. CoRR (2022)
Xiao Wang, Haoqi Fan, Yuandong Tian, Daisuke Kihara, Xinlei Chen
On the Importance of Asymmetry for Siamese Representation Learning. CoRR (2022)
Aaron M. Ferber, Taoan Huang, Daochen Zha, Martin Schubert, Benoit Steiner, Bistra Dilkina, Yuandong Tian
SurCo: Learning Linear Surrogates For Combinatorial Nonlinear Optimization Problems. CoRR (2022)
Kevin Yang, Dan Klein, Nanyun Peng, Yuandong Tian
DOC: Improving Long Story Coherence With Detailed Outline Control. CoRR (2022)
Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu
AutoShard: Automated Embedding Table Sharding for Recommender Systems. KDD (2022)
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian
Multi-objective Optimization by Learning Space Partition. ICLR (2022)
Hui Shi, Sicun Gao, Yuandong Tian, Xinyun Chen, Jishen Zhao
Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and the Explanations. AAAI (2022)
Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian
Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search. IEEE Trans. Pattern Anal. Mach. Intell. 44 (9) (2022)
Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. CoRR (2022)
Minghao Xu, Yuanfan Guo, Yi Xu, Jian Tang, Xinlei Chen, Yuandong Tian
EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data. CoRR (2022)
Yuandong Tian
Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning. CoRR (2022)
Yuandong Tian
Deep Contrastive Learning is Provably (almost) Principal Component Analysis. CoRR (2022)
Taoan Huang, Aaron M. Ferber, Yuandong Tian, Bistra Dilkina, Benoit Steiner
Local Branching Relaxation Heuristics for Integer Linear Programs. CoRR (2022)
Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. CGO (2022)
Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu
DreamShard: Generalizable Embedding Table Placement for Recommender Systems. NeurIPS (2022)
Tongzhou Wang, Simon Du, Antonio Torralba, Phillip Isola, Amy Zhang, Yuandong Tian
Denoised MDPs: Learning World Models Better Than the World Itself. ICML (2022)
Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu
AutoShard: Automated Embedding Table Sharding for Recommender Systems. CoRR (2022)
Cheng Fu, Hanxian Huang, Bram Wasti, Chris Cummins, Riyadh Baghdadi, Kim M. Hazelwood, Yuandong Tian, Jishen Zhao, Hugh Leather
Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition. PACT (2022)
Kevin Yang, Yuandong Tian, Nanyun Peng, Dan Klein
Re3: Generating Longer Stories With Recursive Reprompting and Revision. CoRR (2022)
Yuandong Tian
Understanding Deep Contrastive Learning via Coordinate-wise Optimization. NeurIPS (2022)
Mulong Luo, Wenjie Xiong, Geunbae Lee, Yueying Li, Xiaomeng Yang, Amy Zhang, Yuandong Tian, Hsien-Hsin S. Lee, G. Edward Suh
AutoCAT: Reinforcement Learning for Automated Exploration of Cache Timing-Channel Attacks. CoRR (2022)
Runlong Zhou, Yuandong Tian, Yi Wu, Simon S. Du
Understanding Curriculum Learning in Policy Optimization for Solving Combinatorial Optimization Problems. CoRR (2022)
Xinyun Chen, Dawn Song, Yuandong Tian
Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages. NeurIPS (2021)
Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian
Understanding Robustness in Teacher-Student Setting: A New Perspective. AISTATS (2021)
Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian
NovelD: A Simple yet Effective Exploration Criterion. NeurIPS (2021)
Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli
FP-NAS: Fast Probabilistic Neural Architecture Search. CVPR (2021)
Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph Gonzalez, Stuart Russell
MADE: Exploration via Maximizing Deviation from Explored Regions. CoRR (2021)
Chris Cummins, Bram Wasti, Jiadong Guo, Brandon Cui, Jason Ansel, Sahir Gomez, Somya Jain, Jia Liu, Olivier Teytaud, Benoit Steiner, Yuandong Tian, Hugh Leather
CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. CoRR (2021)
Xiang Wang, Xinlei Chen, Simon S. Du, Yuandong Tian
Towards Demystifying Representation Learning with Non-contrastive Self-supervision. CoRR (2021)
Tianjun Zhang, Paria Rashidinejad, Jiantao Jiao, Yuandong Tian, Joseph E. Gonzalez, Stuart Russell
MADE: Exploration via Maximizing Deviation from Explored Regions. NeurIPS (2021)
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian
Learning Space Partitions for Path Planning. CoRR (2021)
Cheng Fu, Hanxian Huang, Xinyun Chen, Yuandong Tian, Jishen Zhao
Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing. ICML (2021)
Zhuolin Yang, Zhaoxi Chen, Tiffany Cai, Xinyun Chen, Bo Li, Yuandong Tian
Understanding Robustness in Teacher-Student Setting: A New Perspective. CoRR (2021)
Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez
FBNetV3: Joint Architecture-Recipe Search Using Predictor Pretraining. CVPR (2021)
Hui Shi, Sicun Gao, Yuandong Tian, Xinyun Chen, Jishen Zhao
Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and Explanations. CoRR (2021)
Yuandong Tian, Xinlei Chen, Surya Ganguli
Understanding self-supervised Learning Dynamics without Contrastive Pairs. CoRR (2021)
Weilin Cong, Yanhong Wu, Yuandong Tian, Mengting Gu, Yinglong Xia, Mehrdad Mahdavi, Chun-cheng Jason Chen
Dynamic Graph Representation Learning via Graph Transformer Networks. CoRR (2021)
Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
Understanding Dimensional Collapse in Contrastive Self-supervised Learning. CoRR (2021)
Kevin Yang, Tianjun Zhang, Chris Cummins, Brandon Cui, Benoit Steiner, Linnan Wang, Joseph E. Gonzalez, Dan Klein, Yuandong Tian
Learning Space Partitions for Path Planning. NeurIPS (2021)
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Few-Shot Neural Architecture Search. ICML (2021)
Yulai Zhao, Yuandong Tian, Jason D. Lee, Simon S. Du
Provably Efficient Policy Gradient Methods for Two-Player Zero-Sum Markov Games. CoRR (2021)
Xinyun Chen, Dawn Song, Yuandong Tian
Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages. CoRR (2021)
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian
Multi-objective Optimization by Learning Space Partitions. CoRR (2021)
Yuandong Tian, Xinlei Chen, Surya Ganguli
Understanding self-supervised learning dynamics without contrastive pairs. ICML (2021)
Tianyu Li, Roberto Calandra, Deepak Pathak, Yuandong Tian, Franziska Meier, Akshara Rai
Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion. IEEE Robotics Autom. Lett. 6 (2) (2021)
Hang Zhu, Varun Gupta, Satyajeet Singh Ahuja, Yuandong Tian, Ying Zhang, Xin Jin
Network planning with deep reinforcement learning. SIGCOMM (2021)
Yiyang Zhao, Linnan Wang, Yuandong Tian, Rodrigo Fonseca, Tian Guo
Few-shot Neural Architecture Search. CoRR (2020)
Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian
Multi-Agent Collaboration via Reward Attribution Decomposition. CoRR (2020)
Yuandong Tian, Qucheng Gong, Tina Jiang
Joint Policy Search for Multi-agent Collaboration with Imperfect Information. CoRR (2020)
Yuandong Tian, Qucheng Gong, Yu Jiang
Joint Policy Search for Multi-agent Collaboration with Imperfect Information. NeurIPS (2020)
Tianjun Zhang, Huazhe Xu, Xiaolong Wang, Yi Wu, Kurt Keutzer, Joseph E. Gonzalez, Yuandong Tian
BeBold: Exploration Beyond the Boundary of Explored Regions. CoRR (2020)
Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. CoRR (2020)
Cheng Fu, Huili Chen, Zhenheng Yang, Farinaz Koushanfar, Yuandong Tian, Jishen Zhao
Enhancing Model Parallelism in Neural Architecture Search for Multidevice System. IEEE Micro 40 (5) (2020)
Haonan Yu, Sergey Edunov, Yuandong Tian, Ari S. Morcos
Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP. ICLR (2020)
Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli
FP-NAS: Fast Probabilistic Neural Architecture Search. CoRR (2020)
Linnan Wang, Rodrigo Fonseca, Yuandong Tian
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. CoRR (2020)
Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. KDD (2020)
Yuandong Tian, Lantao Yu, Xinlei Chen, Surya Ganguli
Understanding Self-supervised Learning with Dual Deep Networks. CoRR (2020)
Linnan Wang, Rodrigo Fonseca, Yuandong Tian
Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. NeurIPS (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Yuandong Tian