Postdoc HITSZ: Harbin Institute of Technology (Shenzhen) Guangzhou, China Email: cha01nbox AT gmail DOT com [Google Scholar] [Linkedin]

About me

I am a postdoc at HITSZ majoring in Computer Science. I've received the doctor and master degree from Lehigh University in 2023 and 2020, respectively. Before that, I was graduated from Beijing Jiaotong University with the bacholar degree in 2017.

My research interests include Explainable and Robust Machine Learning, Graphical Models, and Nature Language Processing.

Secletive Publications

*: Equal contribution, #: Corresponding.

• Explanation-Guided Adversarial Training for Robust and Interpretable Models.
  Chao Chen, Yanhui Chen, Shanshan Lin, Dongsheng Hong, Shu Wu, Xiangwen Liao, Chuanyi Liu.
  IEEE Transactions On Circuits and Systems For Video Technology (TCSVT)

• BAED: a New Paradigm for Few-shot Graph Learning with Explanation in the Loop.
  Chao Chen*, Xujia Li*, Dongsheng Hong, Shanshan Lin, Xiangwen Liao, Chuanyi Liu, Lei Chen.
  Neural Networks.

• Uncertainty Quantification on Graph Learning.
  Chao Chen*, Chenghua Guo*, Rui Xu*, Cheng Yang, Xiangwen Liao, Xi Zhang, Sihong Xie, Hui Xiong, Philip S. Yu.
  Frontiers of Computer Science (Letter)

• Towards Faithful Sentimental Image Captioning via Evidence-Aware Multi-Agent Reasoning.
  Tiecheng Cai, Zexian Yang, Chao Chen, Shanshan Lin, Xiangwen Liao.
  ICME 2026.

• A Multi-agent System for Zero-Shot Controllable Image Captioning.
  Tiecheng Cai, Chao Chen#, Sibo Ju, Tong Xu, Xiangwen Liao.
  ICASSP 2026.

• Robust Sentiment Analysis via Importance-Guided Augmentation and Consistency Regularization.
  Zhengjue Huang, Tiecheng Cai, Dongsheng Hong, Chao Chen#, Xiangwen Liao.
  ICASSP 2026.

• Cross Paraphrastic invariance learning for hallucination detection.
  Shanshan Lin, Dongsheng Hong, Sibo Ju, Chao Chen, Sihong Xie, Xiangwen Liao.
  ICASSP 2026.

• Constrained paraphrase consistency for LLM hallucination detection.
  Shanshan Lin, Dongsheng Hong, Sibo Ju, Chao Chen, Xi Zhang, Xiangwen Liao.
  ICASSP 2026.

• From Attribution to Action: Jointly ALIGNing Predictions and Explanations.
  Dongsheng Hong*, Chao Chen*, Yanhui Chen, Shanshan Lin, Zhihao Chen, Xiangwen Liao.
  AAAI 2026.

• EMAO: Expectation-Maximization and Adaptive Objective for Microscopic Cascade Prediction.
  Dongsheng Hong, Zhihao Chen, Shanshan Lin, Yanhui Chen, Chao Chen, Wen Lin, Xiangwen Liao.
  NLPCC 2025.

• Fine-Grained Emotion Recognition via In-Context Learning.
  Zhaochun Ren, Zhou Yang, Chenglong Ye, Haizhou Sun, Chao Chen, Xiaofei Zhu and Xiangwen Liao.
  CIKM 2025.

• Wasserstein-Regularized Conformal Prediction under General Distribution Shift.
  Rui Xu, Chao Chen, Yue Sun, Parvathinathan Venkitasubramaniam, Sihong Xie.
  ICLR 2025.

• MSR: A Multifaceted Self-Retrieval Framework for Microscopic Cascade Prediction.
  Dongsheng Hong, Chao Chen, Xujia Li, Shuhui Wang, Wen Lin, Xiangwen Liao.
  AAAI 2025.

• Training for Stable Explanation for Free.
  Chao Chen, Chenghua Guo, Rufeng Chen, Guixiang Ma, Ming Zeng, Xiangwen Liao, Xi Zhang, Sihong Xie.
  NeurIPS 2024.

• Linear Uncertainty Quantification of Graphical Model Inference.
  Chenghua Guo, Han Yu, Jiaxin Liu, Chao Chen, Sihong Xie, Qi Li, Xi Zhang.
  NeurIPS 2024.

• An Iterative Associative Memory Model for Empathetic Response Generation.
  Zhou Yang, Zhaochun Ren, Wang Yufeng, Haizhou Sun, Chao Chen, Xiaofei Zhu, Xiangwen Liao.
  ACL 2024.

• CTSM: Combining Trait and State Emotions for Empathetic Response Model.
  Yufeng Wang, Chao Chen, Zhou Yang, Shuhui Wang, Xiangwen Liao.
  LREC-COLING 2024.

• Self-learn to Explain Siamese Networks Robustly.
  Chao Chen, Yifan Shen, Guixiang Ma, Xiangnan Kong, Srinivas Rangarajan, Xi Zhang, Sihong Xie.
  ICDM 2021.

• Multi-objective Explanations of GNN Predictions.
  Yifei Liu, Chao Chen, Yazheng Liu, Xi Zhang, Sihong Xie.
  ICDM 2021.

• Certification and Trade-off of Multiple Fairness Criteria in Graph-based Spam Detection.
  Kai Burkholder, Kenny Kwock, Sheldon Xu, Jiaxin Liu, Chao Chen, and Sihong Xie.
  CIKM 2021.

• Shapley Values and Meta-Explanations for Probabilistic Graphical Model Inference.
  Yifei Liu, Chao Chen, Xi Zhang, Sihong Xie.
  CIKM 2020.

• Scalable Explanation of Inferences on Large Graphs.
  Chao Chen, Yifei Liu, Xi Zhang, Sihong Xie.
  ICDM, 2019.