Tuo Zhao

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 222

Top Venues

Publications

Yixiao Li, Yifan Yu, Chen Liang, Nikos Karampatziakis, Pengcheng He, Weizhu Chen, Tuo Zhao
LoftQ: LoRA-Fine-Tuning-aware Quantization for Large Language Models. ICLR (2024)
Hao Kang, Qingru Zhang, Souvik Kundu, Geonhwa Jeong, Zaoxing Liu, Tushar Krishna, Tuo Zhao
GEAR: An Efficient KV Cache Compression Recipe for Near-Lossless Generative Inference of LLM. CoRR (2024)
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. ICLR (2024)
Haoyu Wang, Tianci Liu, Tuo Zhao, Jing Gao
RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning. CoRR (2024)
Tuo Zhao, Xinxue Wang, Tingting Zhao, Yuan Wang, Yarui Chen, Jucheng Yang
Hybrid Deep Generative and Sequential Learning Approach for Stock Market Prediction. ICIC (LNAI 5) (2024)
Yan Li, Guanghui Lan, Tuo Zhao
Homotopic policy mirror descent: policy convergence, algorithmic regularization, and improved sample complexity. Math. Program. 207 (1) (2024)
Ilgee Hong, Zichong Li, Alexander Bukharin, Yixiao Li, Haoming Jiang, Tianbao Yang, Tuo Zhao
Adaptive Preference Scaling for Reinforcement Learning with Human Feedback. CoRR (2024)
Zhen Shao, Tuo Zhao, Lin Zhang, Yu Liu
Trust in Digital Commerce: the Moderating Effect of Blockchain Teability Labels. PACIS (2024)
Zi-Hao Qiu, Siqi Guo, Mao Xu, Tuo Zhao, Lijun Zhang, Tianbao Yang
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO. CoRR (2024)
Alexander Bukharin, Ilgee Hong, Haoming Jiang, Qingru Zhang, Zixuan Zhang, Tuo Zhao
Robust Reinforcement Learning from Corrupted Human Feedback. CoRR (2024)
Hoang Huy Nguyen, Yan Li, Tuo Zhao
Stochastic Constrained Decentralized Optimization for Machine Learning with Fewer Data Oracles: a Gradient Sliding Approach. CoRR (2024)
Haoyu Wang, Tuo Zhao, Jing Gao
BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering. CoRR (2024)
Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. ICML (2023)
Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bing Yin, Tuo Zhao
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. ICLR (2023)
Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. ICLR (2023)
Yuqing Wang, Zhenghao Xu, Tuo Zhao, Molei Tao
Good regularity creates large learning rate implicit biases: edge of stability, balancing, and catapult. CoRR (2023)
Xiang Ji, Huazheng Wang, Minshuo Chen, Tuo Zhao, Mengdi Wang
Provable Benefits of Policy Learning from Human Preferences in Contextual Bandit Problems. CoRR (2023)
Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao
HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers. CoRR (2023)
Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. CoRR (2023)
Haoyu Wang, Yaqing Wang, Tianci Liu, Tuo Zhao, Jing Gao
HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference. EMNLP (Findings) (2023)
Zhenghao Xu, Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
Sample Complexity of Neural Policy Mirror Descent for Policy Optimization on Low-Dimensional Manifolds. CoRR (2023)
Alexander Bukharin, Yixiao Li, Pengcheng He, Weizhu Chen, Tuo Zhao
Deep Reinforcement Learning from Hierarchical Weak Preference Feedback. CoRR (2023)
Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. ACL (industry) (2023)
Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. ICML (2023)
Shenao Zhang, Boyi Liu, Zhaoran Wang, Tuo Zhao
Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms. NeurIPS (2023)
Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. EMNLP (Findings) (2023)
Guanghui Lan, Yan Li, Tuo Zhao
Block Policy Mirror Descent. SIAM J. Optim. 33 (3) (2023)
Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. ICML (2023)
Haoyu Wang, Ruirui Li, Haoming Jiang, Zhengyang Wang, Xianfeng Tang, Bin Bi, Monica Xiao Cheng, Bing Yin, Yaqing Wang, Tuo Zhao, Jing Gao
LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models. KDD (2023)
Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao
Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. CoRR (2023)
Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao
Machine Learning Force Fields with Data Cost Aware Training. CoRR (2023)
Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. CoRR (2023)
Kaiqi Zhang, Zixuan Zhang, Minshuo Chen, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang
Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks. CoRR (2023)
Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. ICLR (2023)
Biraj Dahal, Alex Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. CoRR (2023)
Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. CoRR (2023)
Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao
Machine Learning Force Fields with Data Cost Aware Training. ICML (2023)
Alexander Bukharin, Yan Li, Yue Yu, Qingru Zhang, Zhehui Chen, Simiao Zuo, Chao Zhang, Songan Zhang, Tuo Zhao
Robust Multi-Agent Reinforcement Learning via Adversarial Regularization: Theoretical Foundation and Stable Algorithms. NeurIPS (2023)
Zichong Li, Qunzhi Xu, Zhenghao Xu, Yajun Mei, Tuo Zhao, Hongyuan Zha
Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification. CoRR (2023)
Jiachen Yang, Tarik Dzanic, Brenden K. Petersen, Jun Kudo, Ketan Mittal, Vladimir Z. Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio V. Kolev, Robert W. Anderson, Daniel M. Faissol
Reinforcement Learning for Adaptive Mesh Refinement. AISTATS (2023)
Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
Less is More: Task-aware Layer-wise Distillation for Language Model Compression. ICML (2023)
Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. CoRR (2023)
Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou
Module-wise Adaptive Distillation for Multimodality Foundation Models. CoRR (2023)
Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. CoRR (2023)
Qingru Zhang, Chandan Singh, Liyuan Liu, Xiaodong Liu, Bin Yu, Jianfeng Gao, Tuo Zhao
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs. CoRR (2023)
Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation. CoRR (2023)
Zichong Li, Yanbo Xu, Simiao Zuo, Haoming Jiang, Chao Zhang, Tuo Zhao, Hongyuan Zha
SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process. ICML (2023)
Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models. CoRR (2023)
Suliang Bu, Tuo Zhao, Yunxin Zhao
Joint Estimation of DOA and Distance in Noisy Reverberant Conditions. ICASSP (2023)
Alexander Bukharin, Tuo Zhao
Data Diversity Matters for Robust Instruction Tuning. CoRR (2023)
Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang
Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. CoRR (2023)
Chen Liang, Jiahui Yu, Ming-Hsuan Yang, Matthew Brown, Yin Cui, Tuo Zhao, Boqing Gong, Tianyi Zhou
Module-wise Adaptive Distillation for Multimodality Foundation Models. NeurIPS (2023)
Simiao Zuo, Tianyi Liu, Tuo Zhao, Hongyuan Zha
Differentially Private Estimation of Hawkes Process. CoRR (2022)
Simiao Zuo, Xiaodong Liu, Jian Jiao, Denis Charles, Eren Manavoglu, Tuo Zhao, Jianfeng Gao
Efficient Long Sequence Modeling via State Space Augmented Transformer. CoRR (2022)
Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao
Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. ICLR (2022)
Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. AISTATS (2022)
Hao Liu, Haizhao Yang, Minshuo Chen, Tuo Zhao, Wenjing Liao
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces. CoRR (2022)
Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. CoRR (2022)
Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. CoRR (2022)
Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. CoRR (2022)
Jiachen Yang, Ethan Wang, Rakshit Trivedi, Tuo Zhao, Hongyuan Zha
Adaptive Incentive Design with Multi-Agent Meta-Gradient Reinforcement Learning. AAMAS (2022)
Jie Wang, Minshuo Chen, Tuo Zhao, Wenjing Liao, Yao Xie
A Manifold Two-Sample Test Study: Integral Probability Metric with Neural Networks. CoRR (2022)
Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang
CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. CoRR (2022)
Suliang Bu, Tuo Zhao, Yunxin Zhao
TDOA Estimation of Speech Source in Noisy Reverberant Environments. SLT (2022)
Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance. ICML (2022)
Zhen Shao, Lin Zhang, Susan A. Brown, Tuo Zhao
Understanding users' trust transfer mechanism in a blockchain-enabled platform: A mixed methods study. Decis. Support Syst. 155 (2022)
Simiao Zuo, Haoming Jiang, Qingyu Yin, Xianfeng Tang, Bing Yin, Tuo Zhao
DiP-GNN: Discriminative Pre-Training of Graph Neural Networks. CoRR (2022)
Siawpeng Er, Edward Liu, Minshuo Chen, Yan Li, Yuqi Liu, Tuo Zhao, Hua Wang
Deep Learning Assisted End-to-End Synthesis of mm-Wave Passive Networks with 3D EM Structures: A Study on A Transformer-Based Matching Network. CoRR (2022)
Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. NAACL-HLT (2022)
Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. CoRR (2022)
Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. ICML (2022)
Simiao Zuo, Qingyu Yin, Haoming Jiang, Shaohui Xi, Bing Yin, Chao Zhang, Tuo Zhao
Context-Aware Query Rewriting for Improving Users' Search Experience on E-commerce Websites. CoRR (2022)
Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably. CoRR (2022)
Biraj Dahal, Alexander Havrilla, Minshuo Chen, Tuo Zhao, Wenjing Liao
On Deep Generative Models for Approximation and Estimation of Distributions on Manifolds. NeurIPS (2022)
Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation. CoRR (2022)
Yan Li, Tuo Zhao, Guanghui Lan
First-order Policy Optimization for Robust Markov Decision Process. CoRR (2022)
Zhigen Zhao, Simiao Zuo, Tuo Zhao, Ye Zhao
Adversarially Regularized Policy Learning Guided by Trajectory Optimization. L4DC (2022)
Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha
Self-Training with Differentiable Teacher. NAACL-HLT (Findings) (2022)
Suliang Bu, Yunxin Zhao, Tuo Zhao
Steering vector correction in MVDR beamformer for speech enhancement. INTERSPEECH (2022)
Guanghui Lan, Yan Li, Tuo Zhao
Block Policy Mirror Descent. CoRR (2022)
Yan Li, Dhruv Choudhary, Xiaohan Wei, Baichuan Yuan, Bhargav Bhushanam, Tuo Zhao, Guanghui Lan
Frequency-aware SGD for Efficient Embedding Learning with Provable Benefits. ICLR (2022)
Rui Feng, Chen Luo, Qingyu Yin, Bing Yin, Tuo Zhao, Chao Zhang
CERES: Pretraining of Graph-Conditioned Transformer for Semi-Structured Session Data. NAACL-HLT (2022)
Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
Less is More: Task-aware Layer-wise Distillation for Language Model Compression. CoRR (2022)
Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing. ACL (1) (2022)
Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao
Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. CoRR (2022)
Simiao Zuo, Xiaodong Liu, Jian Jiao, Young Jin Kim, Hany Hassan, Ruofei Zhang, Jianfeng Gao, Tuo Zhao
Taming Sparsely Activated Transformer with Stochastic Experts. ICLR (2022)
Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models. ICLR (2022)
Suliang Bu, Yunxin Zhao, Tuo Zhao, Shaojun Wang, Mei Han
Modeling Speech Structure to Improve T-F Masks for Speech Enhancement and Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 30 (2022)
Yan Li, Tuo Zhao, Guanghui Lan
Homotopic Policy Mirror Descent: Policy Convergence, Implicit Regularization, and Improved Sample Complexity. CoRR (2022)
Jiahui Cheng, Minshuo Chen, Hao Liu, Tuo Zhao, Wenjing Liao
High Dimensional Binary Classification under Label Shift: Phase Transition and Regularization. CoRR (2022)
Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong
How Important is the Train-Validation Split in Meta-Learning? ICML (2021)
Haoming Jiang, Danqing Zhang, Tianyu Cao, Bing Yin, Tuo Zhao
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data. CoRR (2021)
Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. CoRR (2021)
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. ICML (2021)
Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. ACL/IJCNLP (1) (2021)
Yan Li, Lingxiao Wang, Jiachen Yang, Ethan Wang, Zhaoran Wang, Tuo Zhao, Hongyuan Zha
Permutation Invariant Policy Optimization for Mean-Field Multi-Agent Reinforcement Learning: A Principled Approach. CoRR (2021)
Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao
Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. CoRR (2021)
Yan Li, Caleb Ju, Ethan X. Fang, Tuo Zhao
Implicit Regularization of Bregman Proximal Point Algorithm and Mirror Descent on Separable Data. CoRR (2021)
Jiachen Yang, Tarik Dzanic, Brenden K. Petersen, Jun Kudo, Ketan Mittal, Vladimir Z. Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio V. Kolev, Robert W. Anderson, Daniel Faissol
Reinforcement Learning for Adaptive Mesh Refinement. CoRR (2021)
Haoming Jiang, Bo Dai, Mengjiao Yang, Tuo Zhao, Wei Wei
Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach. EMNLP (1) (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Tuo Zhao