| 2026 | ACL | BioTool: A Comprehensive Tool-Calling Dataset for Enhancing Biomedical Capabilities of Large Language Models. | Xin Gao, Ruiyi Zhang, Meixi Du, Peijia Qin, Pengtao Xie |
| 2025 | EMNLP | Can Prompts Rewind Time for LLMs? Evaluating the Effectiveness of Prompted Knowledge Cutoffs. | Xin Gao, Ruiyi Zhang, Daniel Du, Saurabh Mahindre, Sai Ashish Somayajula, Pengtao Xie |
| 2025 | EMNLP | Improving the Language Understanding Capabilities of Large Language Models Using Reinforcement Learning. | Sai Ashish Somayajula, Bokai Hu, Qi Cao, Xin Pan, Pengtao Xie |
| 2025 | NAACL | Defense against Prompt Injection Attacks via Mixture of Encodings. | Ruiyi Zhang, David Sullivan, Kyle Jackson, Pengtao Xie, Mei Chen |
| 2024 | ICML | Leverage Class-Specific Accuracy to Guide Data Generation for Improving Image Classification. | Jay Gala, Pengtao Xie |
| 2024 | ICML | Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models. | Mingjia Huo, Sai Ashish Somayajula, Youwei Liang, Ruisi Zhang, Farinaz Koushanfar, Pengtao Xie |
| 2024 | ICML | BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation. | Li Zhang, Youwei Liang, Ruiyi Zhang, Amirhosein Javadi, Pengtao Xie |
| 2024 | NAACL | Generalizable and Stable Finetuning of Pretrained Language Models on Low-Resource Texts. | Sai Ashish Somayajula, Youwei Liang, Li Zhang, Abhishek Singh, Pengtao Xie |
| 2024 | NAACL | AutoLoRA: Automatically Tuning Matrix Ranks in Low-Rank Adaptation Based on Meta Learning. | Ruiyi Zhang, Rushi Qiang, Sai Ashish Somayajula, Pengtao Xie |
| 2023 | AAAI | Joint Self-Supervised Image-Volume Representation Learning with Intra-inter Contrastive Clustering. | Duy M. H. Nguyen, Hoang Nguyen, Truong Thanh Nhat Mai, Tri Cao, Binh T. Nguyen, Nhat Ho, Paul Swoboda, Shadi Albarqouni, Pengtao Xie, Daniel Sonntag |
| 2023 | ICLR | Betty: An Automatic Differentiation Library for Multilevel Optimization. | Sang Keun Choe, Willie Neiswanger, Pengtao Xie, Eric P. Xing |
| 2023 | ICLR | Improving Differentiable Neural Architecture Search by Encouraging Transferability. | Parth Sheth, Pengtao Xie |
| 2023 | ICML | Fair and Accurate Decision Making through Group-Aware Learning. | Ramtin Hosseini, Li Zhang, Bhanu Garg, Pengtao Xie |
| 2023 | ICML | Learning Compiler Pass Orders using Coreset and Normalized Value Prediction. | Youwei Liang, Kevin Stone, Ali Shameli, Chris Cummins, Mostafa Elhoushi, Jiadong Guo, Benoit Steiner, Xiaomeng Yang, Pengtao Xie, Hugh James Leather, Yuandong Tian |
| 2023 | ICML | Improving Bi-level Optimization Based Methods with Inspiration from Humans' Classroom Study Techniques. | Pengtao Xie |
| 2022 | AAAI | Learning from Mistakes - a Framework for Neural Architecture Search. | Bhanu Garg, Li Zhang, Pradyumna Sridhara, Ramtin Hosseini, Eric P. Xing, Pengtao Xie |
| 2022 | ACL | MetaWeighting: Learning to Weight Tasks in Multi-Task Learning. | Yuren Mao, Zekai Wang, Weiwei Liu, Xuemin Lin, Pengtao Xie |
| 2022 | CVPR | Performance-Aware Mutual Knowledge Distillation for Improving Neural Architecture Search. | Pengtao Xie, Xuefeng Du |
| 2022 | ICLR | EViT: Expediting Vision Transformers via Token Reorganizations. | Youwei Liang, Chongjian Ge, Zhan Tong, Yibing Song, Jue Wang, Pengtao Xie |
| 2022 | ICML | Graph Neural Architecture Search Under Distribution Shifts. | Yijian Qin, Xin Wang, Ziwei Zhang, Pengtao Xie, Wenwu Zhu |
| 2021 | AAAI | Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach. | Seo-Jin Bang, Pengtao Xie, Heewook Lee, Wei Wu, Eric P. Xing |
| 2021 | AAAI | Contrastive Self-supervised Learning for Graph Classification. | Jiaqi Zeng, Pengtao Xie |
| 2021 | ACL | Towards Visual Question Answering on Pathology Images. | Xuehai He, Zhuo Cai, Wenlan Wei, Yichen Zhang, Luntian Mou, Eric P. Xing, Pengtao Xie |
| 2021 | ACL | On the Generation of Medical Dialogs for COVID-19. | Meng Zhou, Zechen Li, Bowen Tan, Guangtao Zeng, Wenmian Yang, Xuehai He, Zeqian Ju, Subrato Chakravorty, Shu Chen, Xingyi Yang, Yichen Zhang, Qingyang Wu, Zhou Yu, Kun Xu, Eric P. Xing, Pengtao Xie |
| 2021 | CVPR | DSRNA: Differentiable Search of Robust Neural Architectures. | Ramtin Hosseini, Xingyi Yang, Pengtao Xie |
| 2020 | ECAI | Adversarial Domain Adaptation Being Aware of Class Relationships. | Zeya Wang, Baoyu Jing, Yang Ni, Nanqing Dong, Pengtao Xie, Eric P. Xing |
| 2020 | EMNLP | MedDialog: Large-scale Medical Dialogue Datasets. | Guangtao Zeng, Wenmian Yang, Zeqian Ju, Yue Yang, Sicheng Wang, Ruisi Zhang, Meng Zhou, Jiaqi Zeng, Xiangyu Dong, Ruoyu Zhang, Hongchao Fang, Penghui Zhu, Shu Chen, Pengtao Xie |
| 2020 | IJCAI | Generalized Zero-Shot Text Classification for ICD Coding. | Congzheng Song, Shanghang Zhang, Najmeh Sadoughi, Pengtao Xie, Eric P. Xing |
| 2018 | ACL | A Neural Architecture for Automated ICD Coding. | Pengtao Xie, Haoran Shi, Ming Zhang, Eric P. Xing |
| 2018 | ACL | On the Automatic Generation of Medical Imaging Reports. | Baoyu Jing, Pengtao Xie, Eric P. Xing |
| 2018 | CLOUD | Orpheus: Efficient Distributed Machine Learning via System and Algorithm Co-design. | Pengtao Xie, Jin Kyu Kim, Qirong Ho, Yaoliang Yu, Eric P. Xing |
| 2018 | ICML | Orthogonality-Promoting Distance Metric Learning: Convex Relaxation and Theoretical Analysis. | Pengtao Xie, Wei Wu, Yichen Zhu, Eric P. Xing |
| 2018 | ICML | Nonoverlap-Promoting Variable Selection. | Pengtao Xie, Hongbao Zhang, Yichen Zhu, Eric P. Xing |
| 2017 | ACL | A Constituent-Centric Neural Architecture for Reading Comprehension. | Pengtao Xie, Eric P. Xing |
| 2017 | ICCV | Deep Determinantal Point Process for Large-Scale Multi-label Classification. | Pengtao Xie, Ruslan Salakhutdinov, Luntian Mou, Eric P. Xing |
| 2017 | ICML | Learning Latent Space Models with Angular Constraints. | Pengtao Xie, Yuntian Deng, Yi Zhou, Abhimanu Kumar, Yaoliang Yu, James Zou, Eric P. Xing |
| 2017 | ICML | Uncorrelation and Evenness: a New Diversity-Promoting Regularizer. | Pengtao Xie, Aarti Singh, Eric P. Xing |
| 2017 | IJCAI | Improving the Generalization Performance of Multi-class SVM via Angular Regularization. | Jianxin Li, Haoyi Zhou, Pengtao Xie, Yingchun Zhang |
| 2017 | UAI | Near-Orthogonality Regularization in Kernel Methods. | Pengtao Xie, Barnabs Pczos, Eric P. Xing |
| 2017 | USENIX | Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters. | Hao Zhang, Zeyu Zheng, Shizhen Xu, Wei Dai, Qirong Ho, Xiaodan Liang, Zhiting Hu, Jinliang Wei, Pengtao Xie, Eric P. Xing |
| 2016 | ICML | Diversity-Promoting Bayesian Learning of Latent Variable Models. | Pengtao Xie, Jun Zhu, Eric P. Xing |
| 2016 | UAI | Lighter-Communication Distributed Machine Learning via Sufficient Factor Broadcasting. | Pengtao Xie, Jin Kyu Kim, Yi Zhou, Qirong Ho, Abhimanu Kumar, Yaoliang Yu, Eric P. Xing |
| 2015 | AAAI | Mining User Interests from Personal Photos. | Pengtao Xie, Yulong Pei, Yuan Xie, Eric P. Xing |
| 2015 | AAAI | Integrating Image Clustering and Codebook Learning. | Pengtao Xie, Eric P. Xing |
| 2015 | KDD | Diversifying Restricted Boltzmann Machine for Document Modeling. | Pengtao Xie, Yuntian Deng, Eric P. Xing |
| 2015 | KDD | Petuum: A New Platform for Distributed Machine Learning on Big Data. | Eric P. Xing, Qirong Ho, Wei Dai, Jin Kyu Kim, Jinliang Wei, Seunghak Lee, Xun Zheng, Pengtao Xie, Abhimanu Kumar, Yaoliang Yu |
| 2015 | NAACL | Incorporating Word Correlation Knowledge into Topic Modeling. | Pengtao Xie, Diyi Yang, Eric P. Xing |
| 2013 | IJCAI | Multi-Modal Distance Metric Learning. | Pengtao Xie, Eric P. Xing |
| 2013 | UAI | Integrating Document Clustering and Topic Modeling. | Pengtao Xie, Eric P. Xing |