Sheng Zha

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 38

Top Topics

Differentially Private

Gradient Orientation

Natural Language

Top Venues

DeepLo@EMNLP-IJCNLP

Publications

Dhananjay Ram, Aditya Rawal, Momchil Hardalov, Nikolaos Pappas, Sheng Zha
DEM: Distribution Edited Model for Training with Mixed Data Distributions. CoRR (2024)
Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis
Extreme Miscalibration and the Illusion of Adversarial Robustness. ACL (1) (2024)
Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis
Extreme Miscalibration and the Illusion of Adversarial Robustness. CoRR (2024)
Dingmin Wang, Jinman Zhao, Hengzhi Pei, Samson Tan, Sheng Zha
Fine-tuning Language Models for Joint Rewriting and Completion of Code with Potential Bugs. ACL (Findings) (2024)
Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis
Pre-training Differentially Private Models with Limited Public Data. CoRR (2024)
Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. AAAI (2023)
Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis
Zero redundancy distributed learning with differential privacy. CoRR (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)
Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
Large Language Models of Code Fail at Completing Code with Potential Bugs. NeurIPS (2023)
Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
Large Language Models of Code Fail at Completing Code with Potential Bugs. CoRR (2023)
Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis
On the accuracy and efficiency of group-wise clipping in differentially private optimization. CoRR (2023)
Ruixuan Liu, Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Coupling public and private gradient provably helps optimization. CoRR (2023)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. 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. CoRR (2023)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Optimization on Large Model at Small Cost. ICML (2023)
Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning. NeurIPS (2023)
Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. CoRR (2023)
Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
HYTREL: Hypergraph-enhanced Tabular Data Representation Learning. CoRR (2023)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Bias-Term only Fine-tuning of Foundation Models. CoRR (2022)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. CoRR (2022)
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
Differentially Private Optimization on Large Model at Small Cost. CoRR (2022)
Soumajyoti Sarkar, Kaixiang Lin, Sailik Sengupta, Leonard Lausen, Sheng Zha, Saab Mansour
Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic. CoRR (2022)
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
Meta-learning via Language Model In-context Tuning. ACL (1) (2022)
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT (2022)
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR (2022)
Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. CoRR (2021)
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
Meta-learning via Language Model In-context Tuning. CoRR (2021)
Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. SustaiNLP@EMNLP (2021)
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng, Yi Zhu
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 21 (2020)
Shuai Zheng, Haibin Lin, Sheng Zha, Mu Li
Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes. CoRR (2020)
Jian Guo, He He, Tong He, Leonard Lausen, Mu Li, Haibin Lin, Xingjian Shi, Chenguang Wang, Junyuan Xie, Sheng Zha, Aston Zhang, Hang Zhang, Zhi Zhang, Zhongyue Zhang, Shuai Zheng
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR (2019)
Haibin Lin, Hang Zhang, Yifei Ma, Tong He, Zhi Zhang, Sheng Zha, Mu Li
Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources. CoRR (2019)
Sheng Zha, Ziheng Jiang, Haibin Lin, Zhi Zhang
Just-in-Time Dynamic-Batching. CoRR (2019)
He He, Sheng Zha, Haohan Wang
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. CoRR (2019)
He He, Sheng Zha, Haohan Wang
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. DeepLo@EMNLP-IJCNLP (2019)
Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) (2019)
Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar
Question Type Guided Attention in Visual Question Answering. ECCV (4) (2018)
Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar
Question Type Guided Attention in Visual Question Answering. CoRR (2018)