Joint Boosting Feature Selection for Robust Face Recognition. - Rong Xiao 003; Wu-Jun Li; Yuandong Tian; Xiaoou Tang (CVPR (2), 2006)

EasyAlbum: an interactive photo annotation system based on face clustering and re-ranking. - Jingyu Cui; Fang Wen 001; Rong Xiao 003; Yuandong Tian; Xiaoou Tang (CHI, 2007)

A Face Annotation Framework with Partial Clustering and Interactive Labeling. - Yuandong Tian; Wei Liu 026; Rong Xiao 003; Fang Wen 001; Xiaoou Tang (CVPR, 2007)

Easytoon: an easy and quick tool to personalize a cartoon storyboard using family photo album. - Shifeng Chen; Yuandong Tian; Fang Wen 001; Ying-Qing Xu; Xiaoou Tang (ACM Multimedia, 2008)

(De) focusing on global light transport for active scene recovery. - Mohit Gupta 001; Yuandong Tian; Srinivasa G. Narasimhan; Li Zhang 003 (CVPR, 2009)

Seeing through water: Image restoration using model-based tracking. - Yuandong Tian; Srinivasa G. Narasimhan (ICCV, 2009)

A globally optimal data-driven approach for image distortion estimation. - Yuandong Tian; Srinivasa G. Narasimhan (CVPR, 2010)

Local isomorphism to solve the pre-image problem in kernel methods. - Dong Huang 007; Yuandong Tian; Fernando De la Torre (CVPR, 2011)

Rectification and 3D reconstruction of curved document images. - Yuandong Tian; Srinivasa G. Narasimhan (CVPR, 2011)

Depth from optical turbulence. - Yuandong Tian; Srinivasa G. Narasimhan; Alan Van Nevel (CVPR, 2012)

Exploring the Spatial Hierarchy of Mixture Models for Human Pose Estimation. - Yuandong Tian; C. Lawrence Zitnick; Srinivasa G. Narasimhan (ECCV (5), 2012)

Learning from crowds in the presence of schools of thought. - Yuandong Tian; Jun Zhu 001 (KDD, 2012)

A Combined Theory of Defocused Illumination and Global Light Transport. - Mohit Gupta 001; Yuandong Tian; Srinivasa G. Narasimhan; Li Zhang 003 (Int. J. Comput. Vis., 2012)

Globally Optimal Estimation of Nonrigid Image Distortion. - Yuandong Tian; Srinivasa G. Narasimhan (Int. J. Comput. Vis., 2012)

Integrating Perceptual Learning with External World Knowledge in a Simulated Student. - Nan Li 001; Yuandong Tian; William W. Cohen; Kenneth R. Koedinger (AIED, 2013)

Hierarchical Data-Driven Descent for Efficient Optimal Deformation Estimation. - Yuandong Tian; Srinivasa G. Narasimhan (ICCV, 2013)

Theory and Practice of Globally Optimal Deformation Estimation. - Yuandong Tian (2013)

Scale-invariant learning and convolutional networks. - Soumith Chintala; Marc'Aurelio Ranzato; Arthur Szlam; Yuandong Tian; Mark Tygert; Wojciech Zaremba (CoRR, 2015)

Simple Baseline for Visual Question Answering. - Bolei Zhou; Yuandong Tian; Sainbayar Sukhbaatar; Arthur Szlam; Rob Fergus (CoRR, 2015)

Theory and Practice of Hierarchical Data-driven Descent for Optimal Deformation Estimation. - Yuandong Tian; Srinivasa G. Narasimhan (Int. J. Comput. Vis., 2015)

Single Image 3D Interpreter Network. - Jiajun Wu 001; Tianfan Xue; Joseph J. Lim; Yuandong Tian; Joshua B. Tenenbaum; Antonio Torralba 001; William T. Freeman (ECCV (6), 2016)

Better Computer Go Player with Neural Network and Long-term Prediction. - Yuandong Tian; Yan Zhu 009 (ICLR (Poster), 2016)

Semantic Amodal Segmentation. - Yan Zhu 009; Yuandong Tian; Dimitris N. Metaxas; Piotr Dollár (CVPR, 2017)

Symmetry-Breaking Convergence Analysis of Certain Two-layered Neural Networks with ReLU nonlinearity. - Yuandong Tian (ICLR (Workshop), 2017)

Training Agent for First-Person Shooter Game with Actor-Critic Curriculum Learning. - Yuxin Wu; Yuandong Tian (ICLR (Poster), 2017)

An Analytical Formula of Population Gradient for two-layered ReLU network and its Applications in Convergence and Critical Point Analysis. - Yuandong Tian (ICML, 2017)

ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games. - Yuandong Tian; Qucheng Gong; Wenling Shang; Yuxin Wu; C. Lawrence Zitnick (NIPS, 2017)

Channel-Recurrent Variational Autoencoders. - Wenling Shang; Kihyuk Sohn; Zeynep Akata; Yuandong Tian (CoRR, 2017)

CoDraw: Visual Dialog for Collaborative Drawing. - Jin-Hwa Kim; Devi Parikh; Dhruv Batra; Byoung-Tak Zhang; Yuandong Tian (CoRR, 2017)

When is a Convolutional Filter Easy to Learn? - Simon S. Du; Jason D. Lee; Yuandong Tian (ICLR (Poster), 2018)

Building Generalizable Agents with a Realistic and Rich 3D Environment. - Yi Wu 013; Yuxin Wu; Georgia Gkioxari; Yuandong Tian (ICLR (Workshop), 2018)

Gradient Descent Learns One-hidden-layer CNN: Don't be Afraid of Spurious Local Minima. - Simon S. Du; Jason D. Lee; Yuandong Tian; Aarti Singh; Barnabás Póczos (ICML, 2018)

Channel-Recurrent Autoencoding for Image Modeling. - Wenling Shang; Kihyuk Sohn; Yuandong Tian (WACV, 2018)

Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees. - Huazhe Xu; Yuanzhi Li; Yuandong Tian; Trevor Darrell; Tengyu Ma 001 (CoRR, 2018)

A theoretical framework for deep locally connected ReLU network. - Yuandong Tian (CoRR, 2018)

Learning and Planning with a Semantic Model. - Yi Wu 013; Yuxin Wu; Aviv Tamar; Stuart Russell 001; Georgia Gkioxari; Yuandong Tian (CoRR, 2018)

Learning to Progressively Plan. - Xinyun Chen; Yuandong Tian (CoRR, 2018)

Mixed Precision Quantization of ConvNets via Differentiable Neural Architecture Search. - Bichen Wu; Yanghan Wang; Peizhao Zhang; Yuandong Tian; Peter Vajda; Kurt Keutzer (CoRR, 2018)

3D Interpreter Networks for Viewer-Centered Wireframe Modeling. - Jiajun Wu 001; Tianfan Xue; Joseph J. Lim; Yuandong Tian; Joshua B. Tenenbaum; Antonio Torralba 001; William T. Freeman (Int. J. Comput. Vis., 2018)

Guest Editorial Special Issue on Deep/Reinforcement Learning and Games. - I-Chen Wu; Chang-Shing Lee; Yuandong Tian; Martin Müller 003 (IEEE Trans. Games, 2018)

CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication. - Jin-Hwa Kim; Nikita Kitaev; Xinlei Chen; Marcus Rohrbach; Byoung-Tak Zhang; Yuandong Tian; Dhruv Batra; Devi Parikh (ACL (1), 2019)

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search. - Bichen Wu; Xiaoliang Dai; Peizhao Zhang; Yanghan Wang; Fei Sun; Yiming Wu; Yuandong Tian; Peter Vajda; Yangqing Jia; Kurt Keutzer (CVPR, 2019)

Bayesian Relational Memory for Semantic Visual Navigation. - Yi Wu 013; Yuxin Wu; Aviv Tamar; Stuart Russell 001; Georgia Gkioxari; Yuandong Tian (ICCV, 2019)

Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees. - Yuping Luo; Huazhe Xu; Yuanzhi Li; Yuandong Tian; Trevor Darrell; Tengyu Ma 001 (ICLR (Poster), 2019)

M^3RL: Mind-aware Multi-agent Management Reinforcement Learning. - Tianmin Shu; Yuandong Tian (ICLR (Poster), 2019)

ELF OpenGo: an analysis and open reimplementation of AlphaZero. - Yuandong Tian; Jerry Ma; Qucheng Gong; Shubho Sengupta; Zhuoyuan Chen; James Pinkerton; Larry Zitnick (ICML, 2019)

Learning to Perform Local Rewriting for Combinatorial Optimization. - Xinyun Chen; Yuandong Tian (NeurIPS, 2019)

Coda: An End-to-End Neural Program Decompiler. - Cheng Fu 002; Huili Chen; Haolan Liu; Xinyun Chen; Yuandong Tian; Farinaz Koushanfar; Jishen Zhao (NeurIPS, 2019)

Hierarchical Decision Making by Generating and Following Natural Language Instructions. - Hengyuan Hu; Denis Yarats; Qucheng Gong; Yuandong Tian; Mike Lewis (NeurIPS, 2019)

One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers. - Ari S. Morcos; Haonan Yu; Michela Paganini; Yuandong Tian (NeurIPS, 2019)

AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search. - Linnan Wang; Yiyang Zhao; Yuu Jinnai; Yuandong Tian; Rodrigo Fonseca (CoRR, 2019)

Luck Matters: Understanding Training Dynamics of Deep ReLU Networks. - Yuandong Tian; Tina Jiang; Qucheng Gong; Ari S. Morcos (CoRR, 2019)

Sample-Efficient Neural Architecture Search by Learning Action Space. - Linnan Wang; Saining Xie; Teng Li 009; Rodrigo Fonseca; Yuandong Tian (CoRR, 2019)

A Neural-based Program Decompiler. - Cheng Fu 002; Huili Chen; Haolan Liu; Xinyun Chen; Yuandong Tian; Farinaz Koushanfar; Jishen Zhao (CoRR, 2019)

Over-parameterization as a Catalyst for Better Generalization of Deep ReLU network. - Yuandong Tian (CoRR, 2019)

Neural Architecture Search Using Deep Neural Networks and Monte Carlo Tree Search. - Linnan Wang; Yiyang Zhao; Yuu Jinnai; Yuandong Tian; Rodrigo Fonseca (AAAI, 2020)

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions. - Alvin Wan; Xiaoliang Dai; Peizhao Zhang; Zijian He; Yuandong Tian; Saining Xie; Bichen Wu; Matthew Yu; Tao Xu; Kan Chen; Peter Vajda; Joseph E. Gonzalez (CVPR, 2020)

Deep Symbolic Superoptimization Without Human Knowledge. - Hui Shi; Yang Zhang; Xinyun Chen; Yuandong Tian; Jishen Zhao (ICLR, 2020)

Playing the lottery with rewards and multiple languages: lottery tickets in RL and NLP. - Haonan Yu; Sergey Edunov; Yuandong Tian; Ari S. Morcos (ICLR, 2020)

Student Specialization in Deep Rectified Networks With Finite Width and Input Dimension. - Yuandong Tian (ICML, 2020)

Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. - Qingquan Song; Dehua Cheng; Hanning Zhou; Jiyan Yang; Yuandong Tian; Xia Hu 001 (KDD, 2020)

Joint Policy Search for Multi-agent Collaboration with Imperfect Information. - Yuandong Tian; Qucheng Gong; Yu Jiang (NeurIPS, 2020)

Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Search. - Linnan Wang; Rodrigo Fonseca; Yuandong Tian (NeurIPS, 2020)

FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function. - Xiaoliang Dai; Alvin Wan; Peizhao Zhang; Bichen Wu; Zijian He; Zhen Wei; Kan Chen; Yuandong Tian; Matthew Yu; Peter Vajda; Joseph E. Gonzalez (CoRR, 2020)

Joint Policy Search for Multi-agent Collaboration with Imperfect Information. - Yuandong Tian; Qucheng Gong; Tina Jiang (CoRR, 2020)

Real-world Video Adaptation with Reinforcement Learning. - Hongzi Mao; Shannon Chen; Drew Dimmery; Shaun Singh; Drew Blaisdell; Yuandong Tian; Mohammad Alizadeh; Eytan Bakshy (CoRR, 2020)

Understanding Self-supervised Learning with Dual Deep Networks. - Yuandong Tian; Lantao Yu; Xinlei Chen; Surya Ganguli (CoRR, 2020)

Multi-Agent Collaboration via Reward Attribution Decomposition. - Tianjun Zhang; Huazhe Xu; Xiaolong Wang 004; Yi Wu 013; Kurt Keutzer; Joseph E. Gonzalez; Yuandong Tian (CoRR, 2020)

BeBold: Exploration Beyond the Boundary of Explored Regions. - Tianjun Zhang; Huazhe Xu; Xiaolong Wang 004; Yi Wu 013; Kurt Keutzer; Joseph E. Gonzalez; Yuandong Tian (CoRR, 2020)

Enhancing Model Parallelism in Neural Architecture Search for Multidevice System. - Cheng Fu 002; Huili Chen; Zhenheng Yang; Farinaz Koushanfar; Yuandong Tian; Jishen Zhao (IEEE Micro, 2020)

Understanding Robustness in Teacher-Student Setting: A New Perspective. - Zhuolin Yang; Zhaoxi Chen 004; Tiffany Cai; Xinyun Chen; Bo Li 026; Yuandong Tian (AISTATS, 2021)

FBNetV3: Joint Architecture-Recipe Search Using Predictor Pretraining. - Xiaoliang Dai; Alvin Wan; Peizhao Zhang; Bichen Wu; Zijian He; Zhen Wei; Kan Chen; Yuandong Tian; Matthew Yu; Peter Vajda; Joseph E. Gonzalez (CVPR, 2021)

FP-NAS: Fast Probabilistic Neural Architecture Search. - Zhicheng Yan 001; Xiaoliang Dai; Peizhao Zhang; Yuandong Tian; Bichen Wu; Matt Feiszli (CVPR, 2021)

Learn-to-Share: A Hardware-friendly Transfer Learning Framework Exploiting Computation and Parameter Sharing. - Cheng Fu 002; Hanxian Huang; Xinyun Chen; Yuandong Tian; Jishen Zhao (ICML, 2021)

Understanding self-supervised learning dynamics without contrastive pairs. - Yuandong Tian; Xinlei Chen; Surya Ganguli (ICML, 2021)

Few-Shot Neural Architecture Search. - Yiyang Zhao; Linnan Wang; Yuandong Tian; Rodrigo Fonseca; Tian Guo 001 (ICML, 2021)

Latent Execution for Neural Program Synthesis Beyond Domain-Specific Languages. - Xinyun Chen; Dawn Song; Yuandong Tian (NeurIPS, 2021)

Learning Space Partitions for Path Planning. - Kevin Yang; Tianjun Zhang; Chris Cummins; Brandon Cui; Benoit Steiner; Linnan Wang; Joseph E. Gonzalez; Dan Klein 001; Yuandong Tian (NeurIPS, 2021)

MADE: Exploration via Maximizing Deviation from Explored Regions. - Tianjun Zhang; Paria Rashidinejad; Jiantao Jiao; Yuandong Tian; Joseph E. Gonzalez; Stuart Russell 001 (NeurIPS, 2021)

NovelD: A Simple yet Effective Exploration Criterion. - Tianjun Zhang; Huazhe Xu; Xiaolong Wang 004; Yi Wu 013; Kurt Keutzer; Joseph E. Gonzalez; Yuandong Tian (NeurIPS, 2021)

Network planning with deep reinforcement learning. - Hang Zhu; Varun Gupta; Satyajeet Singh Ahuja; Yuandong Tian; Ying Zhang 022; Xin Jin 008 (SIGCOMM, 2021)

Provably Efficient Policy Gradient Methods for Two-Player Zero-Sum Markov Games. - Yulai Zhao 002; Yuandong Tian; Jason D. Lee; Simon S. Du (CoRR, 2021)

Multi-objective Optimization by Learning Space Partitions. - Yiyang Zhao; Linnan Wang; Kevin Yang; Tianjun Zhang; Tian Guo 001; Yuandong Tian (CoRR, 2021)

Towards Demystifying Representation Learning with Non-contrastive Self-supervision. - Xiang Wang 011; Xinlei Chen; Simon S. Du; Yuandong Tian (CoRR, 2021)

Dynamic Graph Representation Learning via Graph Transformer Networks. - Weilin Cong; Yanhong Wu; Yuandong Tian; Mengting Gu; Yinglong Xia; Mehrdad Mahdavi; Chun-cheng Jason Chen (CoRR, 2021)

Planning in Learned Latent Action Spaces for Generalizable Legged Locomotion. - Tianyu Li; Roberto Calandra; Deepak Pathak; Yuandong Tian; Franziska Meier; Akshara Rai (IEEE Robotics Autom. Lett., 2021)

Q-gym: An Equality Saturation Framework for DNN Inference Exploiting Weight Repetition. - Cheng Fu 002; Hanxian Huang; Bram Wasti; Chris Cummins; Riyadh Baghdadi; Kim M. Hazelwood; Yuandong Tian; Jishen Zhao; Hugh Leather (PACT, 2022)

Learning Bounded Context-Free-Grammar via LSTM and the Transformer: Difference and the Explanations. - Hui Shi; Sicun Gao; Yuandong Tian; Xinyun Chen; Jishen Zhao (AAAI, 2022)

Provably Efficient Policy Optimization for Two-Player Zero-Sum Markov Games. - Yulai Zhao 002; Yuandong Tian; Jason D. Lee; Simon S. Du (AISTATS, 2022)

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research. - Chris Cummins; Bram Wasti; Jiadong Guo; Brandon Cui; Jason Ansel; Sahir Gomez; Somya Jain; Jia Liu; Olivier Teytaud; Benoit Steiner; Yuandong Tian; Hugh Leather (CGO, 2022)

On the Importance of Asymmetry for Siamese Representation Learning. - Xiao Wang; Haoqi Fan 001; Yuandong Tian; Daisuke Kihara; Xinlei Chen (CVPR, 2022)

Re3: Generating Longer Stories With Recursive Reprompting and Revision. - Kevin Yang; Yuandong Tian; Nanyun Peng 001; Dan Klein 001 (EMNLP, 2022)

NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. - Chengyue Gong; Dilin Wang; Meng Li 004; Xinlei Chen; Zhicheng Yan 001; Yuandong Tian; Qiang Liu 001; Vikas Chandra (ICLR, 2022)

Understanding Dimensional Collapse in Contrastive Self-supervised Learning. - Li Jing 001; Pascal Vincent; Yann LeCun; Yuandong Tian (ICLR, 2022)

Multi-objective Optimization by Learning Space Partition. - Yiyang Zhao; Linnan Wang; Kevin Yang; Tianjun Zhang; Tian Guo 001; Yuandong Tian (ICLR, 2022)

Denoised MDPs: Learning World Models Better Than the World Itself. - Tongzhou Wang 001; Simon S. Du; Antonio Torralba 001; Phillip Isola; Amy Zhang 001; Yuandong Tian (ICML, 2022)

AutoShard: Automated Embedding Table Sharding for Recommender Systems. - Daochen Zha; Louis Feng; Bhargav Bhushanam; Dhruv Choudhary; Jade Nie; Yuandong Tian; Jay Chae; Yinbin Ma; Arun Kejariwal; Xia Hu 001 (KDD, 2022)

Understanding Deep Contrastive Learning via Coordinate-wise Optimization. - Yuandong Tian (NeurIPS, 2022)

DreamShard: Generalizable Embedding Table Placement for Recommender Systems. - Daochen Zha; Louis Feng; Qiaoyu Tan; Zirui Liu 001; Kwei-Herng Lai; Bhargav Bhushanam; Yuandong Tian; Arun Kejariwal; Xia Hu 001 (NeurIPS, 2022)

Deep Contrastive Learning is Provably (almost) Principal Component Analysis. - Yuandong Tian (CoRR, 2022)

Understanding Curriculum Learning in Policy Optimization for Solving Combinatorial Optimization Problems. - Runlong Zhou; Yuandong Tian; Yi Wu 013; Simon S. Du (CoRR, 2022)

AutoCAT: Reinforcement Learning for Automated Exploration of Cache Timing-Channel Attacks. - Mulong Luo; Wenjie Xiong 001; Geunbae Lee; Yueying Li; Xiaomeng Yang; Amy Zhang 001; Yuandong Tian; Hsien-Hsin S. Lee; G. Edward Suh (CoRR, 2022)

EurNet: Efficient Multi-Range Relational Modeling of Spatial Multi-Relational Data. - Minghao Xu; Yuanfan Guo; Yi Xu 001; Jian Tang 005; Xinlei Chen; Yuandong Tian (CoRR, 2022)

Sample-Efficient Neural Architecture Search by Learning Actions for Monte Carlo Tree Search. - Linnan Wang; Saining Xie; Teng Li 009; Rodrigo Fonseca; Yuandong Tian (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

DOC: Improving Long Story Coherence With Detailed Outline Control. - Kevin Yang; Dan Klein 001; Nanyun Peng 001; Yuandong Tian (ACL (1), 2023)

Local Branching Relaxation Heuristics for Integer Linear Programs. - Taoan Huang; Aaron M. Ferber; Yuandong Tian; Bistra Dilkina; Benoit Steiner (CPAIOR, 2023)

AutoCAT: Reinforcement Learning for Automated Exploration of Cache-Timing Attacks. - Mulong Luo; Wenjie Xiong 001; Geunbae Lee; Yueying Li; Xiaomeng Yang; Amy Zhang 001; Yuandong Tian; Hsien-Hsin S. Lee; G. Edward Suh (HPCA, 2023)

MACTA: A Multi-agent Reinforcement Learning Approach for Cache Timing Attacks and Detection. - Jiaxun Cui; Xiaomeng Yang; Mulong Luo; Geunbae Lee; Peter Stone 001; Hsien-Hsin S. Lee; Benjamin Lee; G. Edward Suh; Wenjie Xiong 001; Yuandong Tian (ICLR, 2023)

Efficient Planning in a Compact Latent Action Space. - Zhengyao Jiang; Tianjun Zhang; Michael Janner; Yueying Li; Tim Rocktäschel; Edward Grefenstette; Yuandong Tian (ICLR, 2023)

Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning. - Yuandong Tian (ICLR, 2023)

SurCo: Learning Linear SURrogates for COmbinatorial Nonlinear Optimization Problems. - Aaron M. Ferber; Taoan Huang; Daochen Zha; Martin Schubert; Benoit Steiner; Bistra Dilkina; Yuandong Tian (ICML, 2023)

Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning. - Taoan Huang; Aaron M. Ferber; Yuandong Tian; Bistra Dilkina; Benoit Steiner (ICML, 2023)

Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. - Youwei Liang; Kevin Stone; Ali Shameli; Chris Cummins; Mostafa Elhoushi; Jiadong Guo; Benoit Steiner; Xiaomeng Yang; Pengtao Xie; Hugh James Leather; Yuandong Tian (ICML, 2023)

Deja Vu: Contextual Sparsity for Efficient LLMs at Inference Time. - Zichang Liu; Jue Wang; Tri Dao; Tianyi Zhou 002; Binhang Yuan; Zhao Song 002; Anshumali Shrivastava; Ce Zhang 001; Yuandong Tian; Christopher Ré; Beidi Chen (ICML, 2023)

Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models. - Daochen Zha; Louis Feng; Liang Luo; Bhargav Bhushanam; Zirui Liu 001; Yusuo Hu; Jade Nie; Yuzhen Huang; Yuandong Tian; Arun Kejariwal; Xia Hu 001 (MLSys, 2023)

Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer. - Yuandong Tian; Yiping Wang; Beidi Chen; Simon S. Du (NeurIPS, 2023)

H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. - Zhenyu Zhang 015; Ying Sheng 007; Tianyi Zhou 001; Tianlong Chen 001; Lianmin Zheng; Ruisi Cai; Zhao Song 002; Yuandong Tian; Christopher Ré; Clark W. Barrett; Zhangyang Wang; Beidi Chen (NeurIPS, 2023)

Landscape Surrogate: Learning Decision Losses for Mathematical Optimization Under Partial Information. - Arman Zharmagambetov; Brandon Amos; Aaron M. Ferber; Taoan Huang; Bistra Dilkina; Yuandong Tian (NeurIPS, 2023)

DyFormer : A Scalable Dynamic Graph Transformer with Provable Benefits on Generalization Ability. - Weilin Cong; Yanhong Wu; Yuandong Tian; Mengting Gu; Yinglong Xia; Chun-cheng Jason Chen; Mehrdad Mahdavi (SDM, 2023)

Klotski: Efficient and Safe Network Migration of Large Production Datacenters. - Yihao Zhao; Xiaoxiang Zhang; Hang Zhu; Ying Zhang 022; Zhaodong Wang; Yuandong Tian; Alex Nikulkov; Joao Ferreira; Xuanzhe Liu; Xin Jin 008 (SIGCOMM, 2023)

Modeling Scattering Coefficients using Self-Attentive Complex Polynomials with Image-based Representation. - Andrew Cohen; Weiping Dou; Jiang Zhu; Slawomir Koziel; Peter Renner; Jan-Ove Mattsson; Xiaomeng Yang; Beidi Chen; Kevin Stone; Yuandong Tian (CoRR, 2023)

A Cookbook of Self-Supervised Learning. - 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; et al. (CoRR, 2023)

H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models. - Zhenyu Zhang 015; Ying Sheng 007; Tianyi Zhou 002; Tianlong Chen 001; Lianmin Zheng; Ruisi Cai; Zhao Song 002; Yuandong Tian; Christopher Ré; Clark W. Barrett; Zhangyang Wang; Beidi Chen (CoRR, 2023)

Extending Context Window of Large Language Models via Positional Interpolation. - Shouyuan Chen; Sherman Wong; Liangjian Chen; Yuandong Tian (CoRR, 2023)

RLCD: Reinforcement Learning from Contrast Distillation for Language Model Alignment. - Kevin Yang; Dan Klein 001; Asli Celikyilmaz; Nanyun Peng 001; Yuandong Tian (CoRR, 2023)

GenCO: Generating Diverse Solutions to Design Problems with Combinatorial Nature. - Aaron M. Ferber; Arman Zharmagambetov; Taoan Huang; Bistra Dilkina; Yuandong Tian (CoRR, 2023)

Learning Personalized Story Evaluation. - Danqing Wang; Kevin Yang; Hanlin Zhu; Xiaomeng Yang; Andrew Cohen; Lei Li 005; Yuandong Tian (CoRR, 2023)

End-to-end Story Plot Generator. - Hanlin Zhu; Andrew Cohen; Danqing Wang; Kevin Yang; Xiaomeng Yang; Jiantao Jiao; Yuandong Tian (CoRR, 2023)

Understanding Curriculum Learning in Policy Optimization for Online Combinatorial Optimization. - Runlong Zhou; Zelin He; Yuandong Tian; Yi Wu 013; Simon Shaolei Du (Trans. Mach. Learn. Res., 2023)

Learning Personalized Alignment for Evaluating Open-ended Text Generation. - Danqing Wang; Kevin Yang; Hanlin Zhu; Xiaomeng Yang; Andrew Cohen; Lei Li 005; Yuandong Tian (EMNLP, 2024)

H-GAP: Humanoid Control with a Generalist Planner. - Zhengyao Jiang; Yingchen Xu; Nolan Wagener; Yicheng Luo; Michael Janner; Edward Grefenstette; Tim Rocktäschel; Yuandong Tian (ICLR, 2024)

JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention. - Yuandong Tian; Yiping Wang; Zhenyu Zhang 015; Beidi Chen; Simon Shaolei Du (ICLR, 2024)

Efficient Streaming Language Models with Attention Sinks. - Guangxuan Xiao; Yuandong Tian; Beidi Chen; Song Han 003; Mike Lewis (ICLR, 2024)

RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment. - Kevin Yang; Dan Klein 001; Asli Celikyilmaz; Nanyun Peng 001; Yuandong Tian (ICLR, 2024)

LoCoCo: Dropping In Convolutions for Long Context Compression. - Ruisi Cai; Yuandong Tian; Zhangyang Wang; Beidi Chen (ICML, 2024)

GenCO: Generating Diverse Designs with Combinatorial Constraints. - Aaron M. Ferber; Arman Zharmagambetov; Taoan Huang; Bistra Dilkina; Yuandong Tian (ICML, 2024)

Contrastive Predict-and-Search for Mixed Integer Linear Programs. - Taoan Huang; Aaron M. Ferber; Arman Zharmagambetov; Yuandong Tian; Bistra Dilkina (ICML, 2024)

MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases. - Zechun Liu; Changsheng Zhao 002; Forrest N. Iandola; Chen Lai; Yuandong Tian; Igor Fedorov; Yunyang Xiong; Ernie Chang; Yangyang Shi; Raghuraman Krishnamoorthi; Liangzhen Lai; Vikas Chandra (ICML, 2024)

TravelPlanner: A Benchmark for Real-World Planning with Language Agents. - Jian Xie; Kai Zhang 033; Jiangjie Chen; Tinghui Zhu; Renze Lou; Yuandong Tian; Yanghua Xiao; Yu Su 001 (ICML, 2024)

GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection. - Jiawei Zhao; Zhenyu Zhang 015; Beidi Chen; Zhangyang Wang; Anima Anandkumar; Yuandong Tian (ICML, 2024)

On the Surprising Effectiveness of Attention Transfer for Vision Transformers. - Alexander C. Li; Yuandong Tian; Beidi Chen; Deepak Pathak; Xinlei Chen (NeurIPS, 2024)

Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics. - Hanlin Zhu; Baihe Huang; Shaolun Zhang; Michael I. Jordan; Jiantao Jiao; Yuandong Tian; Stuart J. Russell (NeurIPS, 2024)

Image Classifier Based Generative Method for Planar Antenna Design. - Yang Zhong; Weiping Dou; Andrew Cohen; Dia'a Bisharat; Yuandong Tian; Jiang Zhu; Qing Huo Liu (CoRR, 2024)

Diffusion World Model. - Zihan Ding; Amy Zhang 001; Yuandong Tian; Qinqing Zheng (CoRR, 2024)

Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping. - Lucas Lehnert; Sainbayar Sukhbaatar; Paul McVay; Michael Rabbat; Yuandong Tian (CoRR, 2024)

TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding. - Hanshi Sun; Zhuoming Chen; Xinyu Yang 002; Yuandong Tian; Beidi Chen (CoRR, 2024)

Holding the Line: A Study of Writers' Attitudes on Co-creativity with AI. - Morteza Behrooz; Yuandong Tian; William Ngan; Yael Yungster; Justin Wong; David Zax (CoRR, 2024)

AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs. - Anselm Paulus; Arman Zharmagambetov; Chuan Guo 001; Brandon Amos; Yuandong Tian (CoRR, 2024)

From GaLore to WeLore: How Low-Rank Weights Non-uniformly Emerge from Low-Rank Gradients. - Ajay Jaiswal; Lu Yin 006; Zhenyu Zhang 015; Shiwei Liu 003; Jiawei Zhao; Yuandong Tian; Zhangyang Wang (CoRR, 2024)

Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge. - Tianhao Wu 002; Weizhe Yuan; Olga Golovneva; Jing Xu; Yuandong Tian; Jiantao Jiao; Jason Weston; Sainbayar Sukhbaatar (CoRR, 2024)

You Only Use Reactive Attention Slice For Long Context Retrieval. - Yun Joon Soh; Hanxian Huang; Yuandong Tian; Jishen Zhao (CoRR, 2024)

The Perfect Blend: Redefining RLHF with Mixture of Judges. - Tengyu Xu; Eryk Helenowski; Karthik Abinav Sankararaman; Di Jin; Kaiyan Peng; Eric Han; Shaoliang Nie; Chen Zhu; Hejia Zhang; Wenxuan Zhou; Zhouhao Zeng; Yun He; et al. (CoRR, 2024)

Composing Global Optimizers to Reasoning Tasks via Algebraic Objects in Neural Nets. - Yuandong Tian (CoRR, 2024)

Agent-as-a-Judge: Evaluate Agents with Agents. - Mingchen Zhuge; Changsheng Zhao 002; Dylan R. Ashley; Wenyi Wang; Dmitrii Khizbullin; Yunyang Xiong; Zechun Liu; Ernie Chang; Raghuraman Krishnamoorthi; Yuandong Tian; Yangyang Shi; Vikas Chandra; et al. (CoRR, 2024)

To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planning. - Da JU; Song Jiang; Andrew Cohen; Aaron Foss; Sasha Mitts; Arman Zharmagambetov; Brandon Amos; Xian Li 003; Justine T. Kao; Maryam Fazel-Zarandi; Yuandong Tian (CoRR, 2024)

Towards Full Delegation: Designing Ideal Agentic Behaviors for Travel Planning. - Song Jiang; Da JU; Andrew Cohen; Sasha Mitts; Aaron Foss; Justine T. Kao; Xian Li 003; Yuandong Tian (CoRR, 2024)

Training Large Language Models to Reason in a Continuous Latent Space. - Shibo Hao; Sainbayar Sukhbaatar; DiJia Su; Xian Li 003; Zhiting Hu; Jason Weston; Yuandong Tian (CoRR, 2024)

AdvPrefix: An Objective for Nuanced LLM Jailbreaks. - Sicheng Zhu; Brandon Amos; Yuandong Tian; Chuan Guo 001; Ivan Evtimov (CoRR, 2024)

Q-GaLore: Quantized GaLore with INT4 Projection and Layer-Adaptive Low-Rank Gradients. - Zhenyu Zhang 015; Ajay Kumar Jaiswal; Lu Yin 006; Shiwei Liu 003; Jiawei Zhao; Yuandong Tian; Zhangyang Wang (CPAL, 2025)

R-Sparse: Rank-Aware Activation Sparsity for Efficient LLM Inference. - Zhenyu Zhang 015; Zechun Liu; Yuandong Tian; Harshit Khaitan; Zhangyang Wang; Steven Li (ICLR, 2025)

ParamΔ for Direct Mixing: Post-Train Large Language Model At Zero Cost. - Sheng Cao; Mingrui Wu; Karthik Prasad; Yuandong Tian; Zechun Liu (ICLR, 2025)

MagicPIG: LSH Sampling for Efficient LLM Generation. - Zhuoming Chen; Ranajoy Sadhukhan; Zihao Ye; Yang Zhou; Jianyu Zhang; Niklas Nolte; Yuandong Tian; Matthijs Douze; Léon Bottou; Zhihao Jia; Beidi Chen (ICLR, 2025)

Towards General-Purpose Model-Free Reinforcement Learning. - Scott Fujimoto; Pierluca D'Oro; Amy Zhang 001; Yuandong Tian; Michael Rabbat (ICLR, 2025)

SpinQuant: LLM Quantization with Learned Rotations. - Zechun Liu; Changsheng Zhao 002; Igor Fedorov; Bilge Soran; Dhruv Choudhary; Raghuraman Krishnamoorthi; Vikas Chandra; Yuandong Tian; Tijmen Blankevoort (ICLR, 2025)

Sail into the Headwind: Alignment via Robust Rewards and Dynamic Labels against Reward Hacking. - Paria Rashidinejad; Yuandong Tian (ICLR, 2025)

Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces. - DiJia Su; Sainbayar Sukhbaatar; Michael Rabbat; Yuandong Tian; Qinqing Zheng (ICLR, 2025)

Tensor-GaLore: Memory-Efficient Training via Gradient Tensor Decomposition. - Robert Joseph George; David Pitt; Jiawei Zhao; Jean Kossaifi; Cheng Luo; Yuandong Tian; Anima Anandkumar (CoRR, 2025)

Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback. - Yen-Ting Lin; Di Jin; Tengyu Xu; Tianhao Wu 002; Sainbayar Sukhbaatar; Chen Zhu; Yun He; Yun-Nung Chen; Jason Weston; Yuandong Tian; Arash Rahnama; Sinong Wang; et al. (CoRR, 2025)

ParetoQ: Scaling Laws in Extremely Low-bit LLM Quantization. - Zechun Liu; Changsheng Zhao 002; Hanxian Huang; Sijia Chen; Jing Zhang; Jiawei Zhao; Scott Roy; Lisa Jin; Yunyang Xiong; Yangyang Shi; Lin Xiao; Yuandong Tian; et al. (CoRR, 2025)

Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning. - DiJia Su; Hanlin Zhu; Yingchen Xu; Jiantao Jiao; Yuandong Tian; Qinqing Zheng (CoRR, 2025)

GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity? - Yang Zhou; Hongyi Liu; Zhuoming Chen; Yuandong Tian; Beidi Chen (CoRR, 2025)

SHARP: Accelerating Language Model Inference by SHaring Adjacent layers with Recovery Parameters. - Yiping Wang; Hanxian Huang; Yifang Chen 001; Jishen Zhao; Simon Shaolei Du; Yuandong Tian (CoRR, 2025)

LLM Pretraining with Continuous Concepts. - Jihoon Tack; Jack Lanchantin; Jane Yu; Andrew Cohen; Ilia Kulikov; Janice Lan; Shibo Hao; Yuandong Tian; Jason Weston; Xian Li 003 (CoRR, 2025)

Spectral Journey: How Transformers Predict the Shortest Path. - Andrew Cohen; Andrey Gromov; Kaiyu Yang; Yuandong Tian (CoRR, 2025)

NaturalReasoning: Reasoning in the Wild with 2.8M Challenging Questions. - Weizhe Yuan; Jane Yu; Song Jiang; Karthik Padthe; Yang Li; Dong Wang; Ilia Kulikov; Kyunghyun Cho; Yuandong Tian; Jason E. Weston; Xian Li 003 (CoRR, 2025)

SWEET-RL: Training Multi-Turn LLM Agents on Collaborative Reasoning Tasks. - Yifei Zhou; Song Jiang; Yuandong Tian; Jason Weston; Sergey Levine; Sainbayar Sukhbaatar; Xian Li 003 (CoRR, 2025)

GaLore 2: Large-Scale LLM Pre-Training by Gradient Low-Rank Projection. - DiJia Su; Andrew Gu; Jane Xu; Yuandong Tian; Jiawei Zhao (CoRR, 2025)

ParamΔ for Direct Weight Mixing: Post-Train Large Language Model at Zero Cost. - Sheng Cao; Mingrui Wu; Karthik Prasad; Yuandong Tian; Zechun Liu (CoRR, 2025)

Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought. - Hanlin Zhu; Shibo Hao; Zhiting Hu; Jiantao Jiao; Stuart Russell 001; Yuandong Tian (CoRR, 2025)

Deep Think with Confidence. - Yichao Fu; Xuewei Wang; Yuandong Tian; Jiawei Zhao (CoRR, 2025)