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Tianle Cai
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Conference and Workshop Papers
- 2024
- [c11]Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou:
Large Language Models as Tool Makers. ICLR 2024 - 2023
- [c10]Yuhong Li, Tianle Cai, Yi Zhang, Deming Chen, Debadeepta Dey:
What Makes Convolutional Models Great on Long Sequence Modeling? ICLR 2023 - 2021
- [c9]Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei:
A Theory of Label Propagation for Subpopulation Shift. ICML 2021: 1170-1182 - [c8]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: 1204-1215 - [c7]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: 12368-12379 - [c6]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: 22795-22807 - [c5]Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang:
Towards a Theoretical Framework of Out-of-Distribution Generalization. NeurIPS 2021: 23519-23531 - [c4]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: 28877-28888 - 2020
- [c3]Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang:
Locally Differentially Private (Contextual) Bandits Learning. NeurIPS 2020 - [c2]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 - 2019
- [c1]Ruiqi Gao, Tianle Cai, Haochuan Li, Cho-Jui Hsieh, Liwei Wang, Jason D. Lee:
Convergence of Adversarial Training in Overparametrized Neural Networks. NeurIPS 2019: 13009-13020
Informal and Other Publications
- 2024
- [i28]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 abs/2401.10774 (2024) - [i27]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 abs/2402.10193 (2024) - [i26]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 abs/2402.19481 (2024) - [i25]Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, Michael Shieh:
Accelerating Greedy Coordinate Gradient via Probe Sampling. CoRR abs/2403.01251 (2024) - [i24]Yikang Shen, Zhen Guo, Tianle Cai, Zengyi Qin:
JetMoE: Reaching Llama2 Performance with 0.1M Dollars. CoRR abs/2404.07413 (2024) - [i23]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 abs/2404.14469 (2024) - [i22]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 abs/2405.16042 (2024) - [i21]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 abs/2407.20228 (2024) - 2023
- [i20]Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou:
Large Language Models as Tool Makers. CoRR abs/2305.17126 (2023) - [i19]Ziang Song, Tianle Cai, Jason D. Lee, Weijie J. Su:
Reward Collapse in Aligning Large Language Models. CoRR abs/2305.17608 (2023) - [i18]Tianle Cai, Kaixuan Huang, Jason D. Lee, Mengdi Wang:
Scaling In-Context Demonstrations with Structured Attention. CoRR abs/2307.02690 (2023) - [i17]Zhenyu He, Zexuan Zhong, Tianle Cai, Jason D. Lee, Di He:
REST: Retrieval-Based Speculative Decoding. CoRR abs/2311.08252 (2023) - 2022
- [i16]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 abs/2207.09087 (2022) - [i15]Yuhong Li, Tianle Cai, Yi Zhang, Deming Chen, Debadeepta Dey:
What Makes Convolutional Models Great on Long Sequence Modeling? CoRR abs/2210.09298 (2022) - 2021
- [i14]Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang:
Towards Certifying 𝓁∞ Robustness using Neural Networks with 𝓁∞-dist Neurons. CoRR abs/2102.05363 (2021) - [i13]Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei:
A Theory of Label Propagation for Subpopulation Shift. CoRR abs/2102.11203 (2021) - [i12]Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang:
Towards a Theoretical Framework of Out-of-Distribution Generalization. CoRR abs/2106.04496 (2021) - [i11]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 abs/2106.05234 (2021) - [i10]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 abs/2106.08279 (2021) - [i9]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 abs/2106.12566 (2021) - 2020
- [i8]Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang:
Locally Differentially Private (Contextual) Bandits Learning. CoRR abs/2006.00701 (2020) - [i7]Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Liwei Wang:
RANDOM MASK: Towards Robust Convolutional Neural Networks. CoRR abs/2007.14249 (2020) - [i6]Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang:
GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training. CoRR abs/2009.03294 (2020) - [i5]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 abs/2009.11094 (2020) - 2019
- [i4]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 abs/1905.11675 (2019) - [i3]Runtian Zhai
, Tianle Cai, Di He, Chen Dan, Kun He, John E. Hopcroft, Liwei Wang:
Adversarially Robust Generalization Just Requires More Unlabeled Data. CoRR abs/1906.00555 (2019) - [i2]Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee:
Convergence of Adversarial Training in Overparametrized Networks. CoRR abs/1906.07916 (2019) - [i1]Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Di He, Liwei Wang:
Defective Convolutional Layers Learn Robust CNNs. CoRR abs/1911.08432 (2019)
Coauthor Index
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