Publications (Google Scholar)

Preprint

• Gradient-Free Adaptive Global Pruning for Pre-trained Language Models.
  Guangji Bai, Yijiang Li, Chen Ling, Kibaek Kim, Liang Zhao.
  arXiv. Under review.
  [paper]
  

• Beyond Efficiency: A Systematic Survey of Resource-Efficient Large Language Models.
  Guangji Bai, Zheng Chai, Chen Ling, Shiyu Wang, Jiaying Lu, Nan Zhang, Tingwei Shi, Ziyang Yu, Mengdan Zhu, Yifei Zhang, Carl Yang, Yue Cheng, Liang Zhao.
  arXiv. Under review.
  [paper][project page]
  

• Prompt-based Domain Discrimination for Multi-source Time Series Domain Adaptation.
  Junxiang Wang, Guangji Bai, Wei Cheng, Zhengzhang Chen, Liang Zhao, Haifeng Chen.
  arXiv. Under review.
  [paper]
  

• Knowledge-enhanced Neural Machine Reasoning: A Review.
  Tanmoy Chowdhury, Chen Ling, Xuchao Zhang, Xujiang Zhao, Guangji Bai, Jian Pei, Haifeng Chen, Liang Zhao.
  arXiv. Under review.
  [paper]
  

• Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction.
  Guangji Bai, Ziyang Yu*, Zheng Chai, Yue Cheng, Liang Zhao.
  arXiv. Under review.
  [paper][code]
  

• Distributed Graph Neural Network Training with Periodic Stale Representation Synchronization.
  Zheng Chai, Guangji Bai*, Liang Zhao, Yue Cheng.
  arXiv. Under review.
  [paper][code]
  

2024

• Visual Attention-Prompted Prediction and Learning.
  Yifei Zhang, Siyi Gu, Bo Pan, Guangji Bai, Xiaofeng Yang, Liang Zhao.
  2024 International Joint Conference on Artificial Intelligence (IJCAI 2024).
  [paper]
  

• Uncertainty Quantification for In-Context Learning of Large Language Models.
  Chen Ling, Xujiang Zhao, Xuchao Zhang, Wei Cheng, Yanchi Liu, Yiyou Sun, Mika Oishi, Takao Osaki, Katsushi Matsuda, Jie Ji, Guangji Bai, Liang Zhao, Haifeng Chen.
  The North American Chapter of the Association for Computational Linguistics (NAACL 2024 Main Conference).
  [paper][code]
  

2023

• Saliency-Guided Hidden Associative Replay for Continual Learning.
  Guangji Bai, Qilong Zhao, Xiaoyang Jiang, Liang Zhao.
  AMHN Workshop @NeurIPS 2023.
  [paper][code]
  

• Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks.
  Guangji Bai, Chen Ling*, Liang Zhao.
  The Eleventh International Conference on Learning Representations (ICLR 2023, Oral).
  [paper][code]
  

• Saliency-Augmented Memory Completion for Continual Learning.
  Guangji Bai, Chen Ling, Yuyang Gao, Liang Zhao.
  SIAM International Conference on Data Mining (SDM 2023).
  [paper][code]
  

• Sign-Regularized Multi-Task Learning.
  Guangji Bai, Johnny Torres*, Junxiang Wang, Liang Zhao, Carmen Vaca, Cristina Abad.
  SIAM International Conference on Data Mining (SDM 2023).
  [paper][code]
  

• Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs.
  Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang.
  The 39th IEEE International Conference on Data Engineering (ICDE 2023).
  [paper][code]
  

2022

• Deep Spatial Domain Generalization.
  Dazhou Yu, Guangji Bai*, Yun Li, Liang Zhao.
  The 22nd IEEE International Conference on Data Mining (ICDM 2022).
  [paper][code]
  

• RES: A Robust Framework for Guiding Visual Explanation.
  Yuyang Gao, Tong Steven Sun, Guangji Bai, Siyi Gu, Sungsoo Ray Hong, Liang Zhao.
  The 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Research Track, KDD 2022).
  [paper][code]
  

• Saliency-Regularized Deep Multi-Task Learning.
  Guangji Bai, Liang Zhao.
  The 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (Research Track, KDD 2022).
  [paper][code]
  

* equal contribution.