Tianle Cai

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 40

Top Topics

Diffusion Models

Graph Representation

Pruning Methods

Top Venues

Publications

Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou
Large Language Models as Tool Makers. ICLR (2024)
Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, Michael Shieh
Accelerating Greedy Coordinate Gradient via Probe Sampling. CoRR (2024)
Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Ming-Yu Liu, Kai Li, Song Han
DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models. CoRR (2024)
Yikang Shen, Zhen Guo, Tianle Cai, Zengyi Qin
JetMoE: Reaching Llama2 Performance with 0.1M Dollars. CoRR (2024)
Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, Deming Chen
SnapKV: LLM Knows What You are Looking for Before Generation. CoRR (2024)
Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee, Deming Chen, Tri Dao
Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads. CoRR (2024)
Junyan Li, Delin Chen, Tianle Cai, Peihao Chen, Yining Hong, Zhenfang Chen, Yikang Shen, Chuang Gan
FlexAttention for Efficient High-Resolution Vision-Language Models. CoRR (2024)
James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai
BitDelta: Your Fine-Tune May Only Be Worth One Bit. CoRR (2024)
Zhenyu He, Zexuan Zhong, Tianle Cai, Jason D. Lee, Di He
REST: Retrieval-Based Speculative Decoding. NAACL-HLT (2024)
Andrew Li, Xianle Feng, Siddhant Narang, Austin Peng, Tianle Cai, Raj Sanjay Shah, Sashank Varma
Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention. CoRR (2024)
Zhenyu He, Zexuan Zhong, Tianle Cai, Jason D. Lee, Di He
REST: Retrieval-Based Speculative Decoding. CoRR (2023)
Ziang Song, Tianle Cai, Jason D. Lee, Weijie J. Su
Reward Collapse in Aligning Large Language Models. CoRR (2023)
Tianle Cai, Kaixuan Huang, Jason D. Lee, Mengdi Wang
Scaling In-Context Demonstrations with Structured Attention. CoRR (2023)
Yuhong Li, Tianle Cai, Yi Zhang, Deming Chen, Debadeepta Dey
What Makes Convolutional Models Great on Long Sequence Modeling? ICLR (2023)
Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou
Large Language Models as Tool Makers. CoRR (2023)
Yuhong Li, Tianle Cai, Yi Zhang, Deming Chen, Debadeepta Dey
What Makes Convolutional Models Great on Long Sequence Modeling? CoRR (2022)
Yuzheng Hu, Tianle Cai, Jinyong Shan, Shange Tang, Chaochao Cai, Ethan Song, Bo Li, Dawn Song
Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond. CoRR (2022)
Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei
A Theory of Label Propagation for Subpopulation Shift. CoRR (2021)
Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang
Towards a Theoretical Framework of Out-of-Distribution Generalization. NeurIPS (2021)
Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
Do Transformers Really Perform Badly for Graph Representation? NeurIPS (2021)
Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
Do Transformers Really Perform Bad for Graph Representation? CoRR (2021)
Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. NeurIPS (2021)
Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR (2021)
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. ICML (2021)
Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei
A Theory of Label Propagation for Subpopulation Shift. ICML (2021)
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
-dist Neurons. CoRR (2021)
Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track. CoRR (2021)
Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang
Towards a Theoretical Framework of Out-of-Distribution Generalization. CoRR (2021)
Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons. ICML (2021)
Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot. CoRR (2020)
Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang
Locally Differentially Private (Contextual) Bandits Learning. CoRR (2020)
Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee
Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot. NeurIPS (2020)
Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. CoRR (2020)
Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang
Locally Differentially Private (Contextual) Bandits Learning. NeurIPS (2020)
Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Liwei Wang
RANDOM MASK: Towards Robust Convolutional Neural Networks. CoRR (2020)
Tianle Cai, Ruiqi Gao, Jikai Hou, Siyu Chen, Dong Wang, Di He, Zhihua Zhang, Liwei Wang
A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems. CoRR (2019)
Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John E. Hopcroft, Liwei Wang
Adversarially Robust Generalization Just Requires More Unlabeled Data. CoRR (2019)
Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Di He, Liwei Wang
Defective Convolutional Layers Learn Robust CNNs. CoRR (2019)
Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee
Convergence of Adversarial Training in Overparametrized Networks. CoRR (2019)
Ruiqi Gao, Tianle Cai, Haochuan Li, Cho-Jui Hsieh, Liwei Wang, Jason D. Lee
Convergence of Adversarial Training in Overparametrized Neural Networks. NeurIPS (2019)