| 2025 | NAACL | Sequence-level Large Language Model Training with Contrastive Preference Optimization. | Zhili Feng, Dhananjay Ram, Cole Hawkins, Aditya Rawal, Jinman Zhao, Sheng Zha |
| 2024 | ACL | Extreme Miscalibration and the Illusion of Adversarial Robustness. | Vyas Raina, Samson Tan, Volkan Cevher, Aditya Rawal, Sheng Zha, George Karypis |
| 2024 | ACL | Fine-tuning Language Models for Joint Rewriting and Completion of Code with Potential Bugs. | Dingmin Wang, Jinman Zhao, Hengzhi Pei, Samson Tan, Sheng Zha |
| 2024 | EMNLP | DEM: Distribution Edited Model for Training with Mixed Data Distributions. | Dhananjay Ram, Aditya Rawal, Momchil Hardalov, Nikolaos Pappas, Sheng Zha |
| 2024 | ICML | Differentially Private Bias-Term Fine-tuning of Foundation Models. | Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis |
| 2023 | AAAI | Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion. | Hengzhi Pei, Jinman Zhao, Leonard Lausen, Sheng Zha, George Karypis |
| 2023 | EMNLP | Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer. | Qingru Zhang, Dhananjay Ram, Cole Hawkins, Sheng Zha, Tuo Zhao |
| 2023 | ICML | Differentially Private Optimization on Large Model at Small Cost. | Zhiqi Bu, Yu-Xiang Wang, Sheng Zha, George Karypis |
| 2022 | ACL | Meta-learning via Language Model In-context Tuning. | Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He |
| 2022 | NAACL | Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning. | Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros, Sheng Zha, He He, George Karypis |
| 2021 | EMNLP | Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing. | Haoyu He, Xingjian Shi, Jonas Mueller, Sheng Zha, Mu Li, George Karypis |
| 2019 | EMNLP | Dive into Deep Learning for Natural Language Processing. | Haibin Lin, Xingjian Shi, Leonard Lausen, Aston Zhang, He He, Sheng Zha, Alexander J. Smola |
| 2018 | ECCV | Question Type Guided Attention in Visual Question Answering. | Yang Shi, Tommaso Furlanello, Sheng Zha, Animashree Anandkumar |