Tianle Cai

According to our database, Tianle Cai authored at least 33 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Training-Free Activation Sparsity in Large Language Models.

James Liu, Pragaash Ponnusamy, Tianle Cai, Han Guo, Yoon Kim, Ben Athiwaratkun

CoRR, 2024

Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attention.

Andrew Li, Xianle Feng, Siddhant Narang, Austin Peng, Tianle Cai, Raj Sanjay Shah, Sashank Varma

CoRR, 2024

SnapKV: LLM Knows What You are Looking for Before Generation.

Yuhong Li, Yingbing Huang, Bowen Yang, Bharat Venkitesh, Acyr Locatelli, Hanchen Ye, Tianle Cai, Patrick Lewis, Deming Chen

CoRR, 2024

JetMoE: Reaching Llama2 Performance with 0.1M Dollars.

Yikang Shen, Zhen Guo, Tianle Cai, Zengyi Qin

CoRR, 2024

Accelerating Greedy Coordinate Gradient via Probe Sampling.

Yiran Zhao, Wenyue Zheng, Tianle Cai, Xuan Long Do, Kenji Kawaguchi, Anirudh Goyal, Michael Shieh

CoRR, 2024

DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models.

Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Ming-Yu Liu, Kai Li, Song Han

CoRR, 2024

BitDelta: Your Fine-Tune May Only Be Worth One Bit.

James Liu, Guangxuan Xiao, Kai Li, Jason D. Lee, Song Han, Tri Dao, Tianle Cai

CoRR, 2024

REST: Retrieval-Based Speculative Decoding.

Zhenyu He, Zexuan Zhong, Tianle Cai, Jason D. Lee, Di He

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee, Deming Chen, Tri Dao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Large Language Models as Tool Makers.

Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou

Proceedings of the Twelfth International Conference on Learning Representations, 2024

FlexAttention for Efficient High-Resolution Vision-Language Models.

Junyan Li, Delin Chen, Tianle Cai, Peihao Chen, Yining Hong, Zhenfang Chen, Yikang Shen, Chuang Gan

Proceedings of the Computer Vision - ECCV 2024, 2024

DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models.

Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Kai Li, Song Han

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Scaling In-Context Demonstrations with Structured Attention.

Tianle Cai, Kaixuan Huang, Jason D. Lee, Mengdi Wang

CoRR, 2023

Reward Collapse in Aligning Large Language Models.

Ziang Song, Tianle Cai, Jason D. Lee, Weijie J. Su

CoRR, 2023

What Makes Convolutional Models Great on Long Sequence Modeling?

Yuhong Li, Tianle Cai, Yi Zhang, Deming Chen, Debadeepta Dey

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Is Vertical Logistic Regression Privacy-Preserving? A Comprehensive Privacy Analysis and Beyond.

Yuzheng Hu, Tianle Cai, Jinyong Shan, Shange Tang, Chaochao Cai, Ethan Song, Bo Li, Dawn Song

CoRR, 2022

2021

First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track.

Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He

CoRR, 2021

Do Transformers Really Perform Bad for Graph Representation?

Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

CoRR, 2021

Towards Certifying 𝓁_∞ Robustness using Neural Networks with 𝓁_∞-dist Neurons.

Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang

CoRR, 2021

Do Transformers Really Perform Badly for Graph Representation?

Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards a Theoretical Framework of Out-of-Distribution Generalization.

Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding.

Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons.

Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training.

Tianle Cai, Shengjie Luo, Keyulu Xu, Di He, Tie-Yan Liu, Liwei Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

A Theory of Label Propagation for Subpopulation Shift.

Tianle Cai, Ruiqi Gao, Jason D. Lee, Qi Lei

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

RANDOM MASK: Towards Robust Convolutional Neural Networks.

Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Liwei Wang

CoRR, 2020

Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot.

Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Locally Differentially Private (Contextual) Bandits Learning.

Kai Zheng, Tianle Cai, Weiran Huang, Zhenguo Li, Liwei Wang

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Defective Convolutional Layers Learn Robust CNNs.

Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Di He, Liwei Wang

CoRR, 2019

Convergence of Adversarial Training in Overparametrized Networks.

Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee

CoRR, 2019

Adversarially Robust Generalization Just Requires More Unlabeled Data.

Runtian Zhai, Tianle Cai, Di He, Chen Dan, Kun He, John E. Hopcroft, Liwei Wang

CoRR, 2019

A Gram-Gauss-Newton Method Learning Overparameterized Deep Neural Networks for Regression Problems.

Tianle Cai, Ruiqi Gao, Jikai Hou, Siyu Chen, Dong Wang, Di He, Zhihua Zhang, Liwei Wang

CoRR, 2019

Convergence of Adversarial Training in Overparametrized Neural Networks.

Ruiqi Gao, Tianle Cai, Haochuan Li, Cho-Jui Hsieh, Liwei Wang, Jason D. Lee

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019