Sheng Zha - RankMe

46 papers A* 8Journal 26Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	Sequence-level Large Language Model Training with Contrastive Preference Optimization. NAACL (Findings) Zhili Feng, Dhananjay Ram, Cole Hawkins, Aditya Rawal, Jinman Zhao, Sheng Zha
2025	J	`jnl`	Sequence-level Large Language Model Training with Contrastive Preference Optimization. CoRR Zhili Feng, Dhananjay Ram, Cole Hawkins, Aditya Rawal, Jinman Zhao, Sheng Zha
2024	A*	`conf`	DEM: Distribution Edited Model for Training with Mixed Data Distributions. EMNLP Dhananjay Ram, Aditya Rawal, Momchil Hardalov, Nikolaos Pappas, Sheng Zha
2024	J	`jnl`	DEM: Distribution Edited Model for Training with Mixed Data Distributions. CoRR Dhananjay Ram, Aditya Rawal, Momchil Hardalov, Nikolaos Pappas, Sheng Zha
2024	A*	`conf`	Differentially Private Bias-Term Fine-tuning of Foundation Models. ICML Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
2024	—	`conf`	Extreme Miscalibration and the Illusion of Adversarial Robustness. ACL (1) Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis
2024	J	`jnl`	Extreme Miscalibration and the Illusion of Adversarial Robustness. CoRR Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis
2024	—	`conf`	Fine-tuning Language Models for Joint Rewriting and Completion of Code with Potential Bugs. ACL (Findings) Dingmin Wang, Jinman Zhao, Hengzhi Pei, Samson Tan, Sheng Zha
2024	A*	`conf`	Pre-training Differentially Private Models with Limited Public Data. NeurIPS Zhiqi Bu, Xinwei Zhang, Sheng Zha, Mingyi Hong, George Karypis
2024	J	`jnl`	Pre-training Differentially Private Models with Limited Public Data. CoRR Zhiqi Bu, Xinwei Zhang, Mingyi Hong, Sheng Zha, George Karypis
2024	—	`conf`	Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning. ENLSP Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher, Thomas Brox, Sheng Zha, George Karypis
2024	J	`jnl`	Revisiting SMoE Language Models by Evaluating Inefficiencies with Task Specific Expert Pruning. CoRR Soumajyoti Sarkar, Leonard Lausen, Volkan Cevher, Sheng Zha, Thomas Brox, George Karypis
2023	A*	`conf`	Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. NeurIPS Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
2023	A*	`conf`	Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. AAAI Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. CoRR Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	Coupling public and private gradient provably helps optimization. CoRR Ruixuan Liu, Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
2023	A*	`conf`	Differentially Private Optimization on Large Model at Small Cost. ICML Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
2023	—	`conf`	Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. EMNLP (Findings) Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
2023	J	`jnl`	Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. CoRR Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao
2023	J	`jnl`	HYTREL: Hypergraph-enhanced Tabular Data Representation Learning. CoRR Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
2023	A*	`conf`	HyTrel: Hypergraph-enhanced Tabular Data Representation Learning. NeurIPS Pei Chen, Soumajyoti Sarkar, Leonard Lausen, Balasubramaniam Srinivasan, Sheng Zha, Ruihong Huang, George Karypis
2023	A*	`conf`	Large Language Models of Code Fail at Completing Code with Potential Bugs. NeurIPS Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	Large Language Models of Code Fail at Completing Code with Potential Bugs. CoRR Tuan Dinh, Jinman Zhao, Samson Tan, Renato Negrinho, Leonard Lausen, Sheng Zha, George Karypis
2023	J	`jnl`	On the accuracy and efficiency of group-wise clipping in differentially private optimization. CoRR Zhiqi Bu, Ruixuan Liu, Yu-Xiang Wang, Sheng Zha, George Karypis
2023	—	`conf`	Python Array API Standard: Toward Array Interoperability in the Scientific Python Ecosystem. SciPy Aaron Meurer, Athan Reines, Ralf Gommers, Yao-Lung L. Fang, John Kirkham, Matthew Barber, Stephan Hoyer, Andreas Müller, Sheng Zha, Saul Shanabrook, Stephannie Jiménez Gacha, Mario Lezcano Casado, Thomas J. Fan, Tyler Reddy, Alexandre Passos, Hyukjin Kwon, Travis E. Oliphant, Consortium for Python Data API Standards
2023	J	`jnl`	Zero redundancy distributed learning with differential privacy. CoRR Zhiqi Bu, Justin Chiu, Ruixuan Liu, Sheng Zha, George Karypis
2022	J	`jnl`	Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger. CoRR Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
2022	J	`jnl`	Differentially Private Bias-Term only Fine-tuning of Foundation Models. CoRR Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
2022	J	`jnl`	Differentially Private Optimization on Large Model at Small Cost. CoRR Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis
2022	—	`conf`	Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. NAACL-HLT Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
2022	J	`jnl`	Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. CoRR Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis
2022	—	`conf`	Meta-learning via Language Model In-context Tuning. ACL (1) Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
2022	J	`jnl`	Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic. CoRR Soumajyoti Sarkar, Kaixiang Lin, Sailik Sengupta, Leonard Lausen, Sheng Zha, Saab Mansour
2021	—	`conf`	Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. SustaiNLP@EMNLP Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
2021	J	`jnl`	Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. CoRR Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis
2021	J	`jnl`	Meta-learning via Language Model In-context Tuning. CoRR Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
2020	J	`jnl`	Accelerated Large Batch Optimization of BERT Pretraining in 54 minutes. CoRR Shuai Zheng, Haibin Lin, Sheng Zha, Mu Li
2020	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. J. Mach. Learn. Res. 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
2019	—	`conf`	Dive into Deep Learning for Natural Language Processing. EMNLP/IJCNLP (2) Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola
2019	J	`jnl`	Dynamic Mini-batch SGD for Elastic Distributed Training: Learning in the Limbo of Resources. CoRR Haibin Lin, Hang Zhang, Yifei Ma, Tong He, Zhi Zhang, Sheng Zha, Mu Li
2019	J	`jnl`	GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing. CoRR 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
2019	J	`jnl`	Just-in-Time Dynamic-Batching. CoRR Sheng Zha, Ziheng Jiang, Haibin Lin, Zhi Zhang
2019	—	`conf`	Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. DeepLo@EMNLP-IJCNLP He He, Sheng Zha, Haohan Wang
2019	J	`jnl`	Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual. CoRR He He, Sheng Zha, Haohan Wang
2018	—	`conf`	Question Type Guided Attention in Visual Question Answering. ECCV (4) Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar
2018	J	`jnl`	Question Type Guided Attention in Visual Question Answering. CoRR Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar