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Yiwei Wang

Postdoc
UCLA
yiweiwang2@ucmerced.edu


About Me

I will join the Department of Computer Science at University of California, Merced as an Assistant Professor in the Spring of 2025.

Recruiting Ph.D. students and (remote) research interns. I’m actively looking for students at all levels interested in large language models’ research. If you are interested, please feel free to email me.

I am currently a Postdoc at UCLA advised by Prof. Kai-Wei Chang and Prof. Nanyun Peng. I received my Ph.D. in Computer Science at National University of Singapore, where I was fortunate to be advised by Prof. Bryan Hooi and collaborate with Prof. Muhao Chen. My recent research is focused on trustworthy large language models.

Selected Publications [Google Scholar][DBLP]

    2025

  1. COLING
    "Not Aligned" is Not" Malicious": Being Careful about Hallucinations of Large Language Models' Jailbreak
    Lingrui Mei, Shenghua Liu, Yiwei Wang, Baolong Bi, Jiayi Mao, Xueqi Cheng.
    International Conference on Computational Linguistics (COLING), 2025.
    PDF Code
  2. COLING
    Con-ReCall: Detecting Pre-training Data in LLMs via Contrastive Decoding
    Cheng Wang, Yiwei Wang, Bryan Hooi, Yujun Cai, Nanyun Peng, Kai-Wei Chang.
    International Conference on Computational Linguistics (COLING), 2025.
    PDF Code

    3. 2024

  3. Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification
    Yihong Luo, Yuhan Chen, Siya Qiu, Yiwei Wang, Chen Zhang, Yan Zhou, Xiaochun Cao, Jing Tang.
    Advances in Neural Information Processing Systems (NeurIPS), 2024.
    PDF Code
  4. Adaptive Token Biaser: Knowledge Editing via Biasing Key Entities
    Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Hongcheng Gao, Yilong Xu, Xueqi Cheng.
    Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
    PDF Code
  5. EMNLP
    Control Large Language Models via Divide-and-Conquer
    Bingxuan Li, Yiwei Wang, Tao Meng, Nanyun Peng, Kai-Wei Chang.
    Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
    PDF Code
  6. SLANG: New Concept Comprehension of Large Language Models
    Lingrui Mei, Shenghua Liu, Yiwei Wang, Baolong Bi, Xueqi Chen.
    Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
    PDF Code
  7. AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations
    Zhicheng Yang, Yinya Huang, Jing Xiong, Liang Feng, Xiaodan Liang, Yiwei Wang, Jing Tang.
    Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
    PDF Code
  8. EMNLP
    LLM-A* : Large Language Model Enhanced Incremental Heuristic Search on Path Planning
    Silin Meng, Yiwei Wang, Cheng-Fu Yang, Nanyun Peng, Kai-Wei Chang.
    Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024.
    PDF Code
  9. ACL
    Lpnl: Scalable link prediction with large language models
    Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Xueqi Cheng.
    Association for Computational Linguistics ACL 2024, 2024.
    PDF Code
  10. Scalable and Effective Implicit Graph Neural Networks on Large Graphs
    Juncheng Liu, Bryan Hooi, Kenji Kawaguchi, Yiwei Wang, Chaosheng Dong, Xiaokui Xiao.
    The Twelfth International Conference on Learning Representations (ICLR), 2024.
    PDF Code
  11. Decoding by Contrasting Knowledge: Enhancing LLMs' Confidence on Edited Facts
    Baolong Bi, Shenghua Liu, Lingrui Mei, Yiwei Wang, Pengliang Ji, Xueqi Cheng.
    arXiv preprint arXiv:2405.11613, 2024.
    PDF Code
  12. Is factuality decoding a free lunch for llms? evaluation on knowledge editing benchmark
    Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Xueqi Cheng.
    arXiv preprint arXiv:2404.00216, 2024.
    PDF Code
  13. UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting
    Juncheng Liu, Chenghao Liu, Gerald Woo, Yiwei Wang, Bryan Hooi, Caiming Xiong, Doyen Sahoo.
    arXiv preprint arXiv:2406.04975, 2024.
    PDF Code
  14. Preprint
    Deepedit: Knowledge editing as decoding with constraints
    Yiwei Wang, Muhao Chen, Nanyun Peng, Kai-Wei Chang.
    arXiv preprint arXiv:2401.10471, 2024.
    PDF Code
  15. Vulnerability of Large Language Models to Output Prefix Jailbreaks: Impact of Positions on Safety
    Yiwei Wang, Muhao Chen, Nanyun Peng, Kai-Wei Chang.
    Authorea Preprints, 2024.
    PDF Code
  16. Think Carefully and Check Again! Meta-Generation Unlocking LLMs for Low-Resource Cross-Lingual Summarization
    Zhecheng Li, Yiwei Wang, Bryan Hooi, Yujun Cai, Naifan Cheung, Nanyun Peng, Kai-wei Chang.
    arXiv preprint arXiv:2410.20021, 2024.
    PDF Code
  17. Can Graph Descriptive Order Affect Solving Graph Problems with LLMs?
    Yuyao Ge, Shenghua Liu, Baolong Bi, Yiwei Wang, Lingrui Mei, Wenjie Feng, Lizhe Chen, Xueqi Cheng.
    Preprint, 2024.
    PDF Code

    18. 2023

  18. A Causal View of Entity Bias in (Large) Language Models
    Fei Wang, Wenjie Mo, Yiwei Wang, Wenxuan Zhou, Muhao Chen.
    Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.
    PDF Code
  19. EMNLP
    Primacy Effect of ChatGPT
    Yiwei Wang, Yujun Cai, Muhao Chen, Yuxuan Liang, Bryan Hooi.
    Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023.
    PDF Code
  20. Airformer: Predicting nationwide air quality in china with transformers
    Yuxuan Liang, Yutong Xia, Songyu Ke, Yiwei Wang, Qingsong Wen, Junbo Zhang, Yu Zheng, Roger Zimmermann.
    Proceedings of the AAAI Conference on Artificial Intelligence, 2023.
    PDF Code
  21. How Fragile is Relation Extraction under Entity Replacements?
    Yiwei Wang, Bryan Hooi, Fei Wang, Yujun Cai, Yuxuan Liang, Wenxuan Zhou, Jing Tang, Manjuan Duan, Muhao Chen.
    CONLL 2023, 2023.
    PDF Code
  22. Graph explicit neural networks: Explicitly encoding graphs for efficient and accurate inference
    Yiwei Wang, Bryan Hooi, Yozen Liu, Neil Shah.
    Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (WSDM), 2023.
    PDF Code

    23. 2022

  23. Dangling-Aware Entity Alignment with Mixed High-Order Proximities
    Juncheng Liu, Zequn Sun, Bryan Hooi, Yiwei Wang, Dayiheng Liu, Baosong Yang, Xiaokui Xiao, Muhao Chen.
    Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
    PDF Code
  24. GraphCache: Message Passing as Caching for Sentence-Level Relation Extraction
    Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Bryan Hooi.
    Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
    PDF Code
  25. Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis
    Yiwei Wang, Muhao Chen, Wenxuan Zhou, Yujun Cai, Yuxuan Liang, Dayiheng Liu, Baosong Yang, Juncheng Liu, Bryan Hooi.
    Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2022.
    PDF Code
  26. Mixed-order relation-aware recurrent neural networks for spatio-temporal forecasting
    Yuxuan Liang, Kun Ouyang, Yiwei Wang, Zheyi Pan, Yifang Yin, Hongyang Chen, Junbo Zhang, Yu Zheng, David S Rosenblum, Roger Zimmermann.
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
    PDF Code
  27. Lscale: latent space clustering-based active learning for node classification
    Juncheng Liu, Yiwei Wang, Bryan Hooi, Renchi Yang, Xiaokui Xiao.
    Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), 2022.
    PDF Code
  28. Flashlight: Scalable link prediction with effective decoders
    Yiwei Wang, Bryan Hooi, Yozen Liu, Tong Zhao, Zhichun Guo, Neil Shah.
    Learning on Graphs Conference (LOG), 2022.
    PDF Code

    29. 2021

  29. Eignn: Efficient infinite-depth graph neural networks
    Juncheng Liu, Kenji Kawaguchi, Bryan Hooi, Yiwei Wang, Xiaokui Xiao.
    Advances in Neural Information Processing Systems (NeurIPS), 2021.
    PDF Code
  30. Adaptive data augmentation on temporal graphs
    Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Siddharth Bhatia, Bryan Hooi.
    Advances in Neural Information Processing Systems (NeurIPS), 2021.
    PDF Code
  31. A unified 3d human motion synthesis model via conditional variational auto-encoder
    Yujun Cai, Yiwei Wang, Yiheng Zhu, Tat-Jen Cham, Jianfei Cai, Junsong Yuan, Jun Liu, Chuanxia Zheng, Sijie Yan, Henghui Ding, others.
    Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021.
    PDF Code
  32. Structure-aware label smoothing for graph neural networks
    Yiwei Wang, Yujun Cai, Yuxuan Liang, Wei Wang, Henghui Ding, Muhao Chen, Jing Tang, Bryan Hooi.
    arXiv preprint arXiv:2112.00499, 2021.
    PDF Code
  33. Time-aware neighbor sampling for temporal graph networks
    Yiwei Wang, Yujun Cai, Yuxuan Liang, Henghui Ding, Changhu Wang, Bryan Hooi.
    2022 International Joint Conference on Neural Networks (IJCNN), 2021.
    PDF Code
  34. Fine-grained urban flow prediction
    Yuxuan Liang, Kun Ouyang, Junkai Sun, Yiwei Wang, Junbo Zhang, Yu Zheng, David Rosenblum, Roger Zimmermann.
    Proceedings of the Web Conference 2021, 2021.
    PDF Code
  35. Modeling Trajectories with Neural Ordinary Differential Equations.
    Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann.
    IJCAI, 2021.
    PDF Code
  36. Revisiting convolutional neural networks for citywide crowd flow analytics
    Yuxuan Liang, Kun Ouyang, Yiwei Wang, Ye Liu, Junbo Zhang, Yu Zheng, David S Rosenblum.
    Machine Learning and Knowledge Discovery in Databases: European Conference, (ECML-PKDD), 2021.
    PDF Code
  37. Curgraph: Curriculum learning for graph classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi.
    Proceedings of the Web Conference 2021 (WWW), 2021.
    PDF Code
  38. Mixup for node and graph classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi.
    Proceedings of the Web Conference 2021 (WWW), 2021.
    PDF Code
  39. Progressive supervision for node classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi.
    Machine Learning and Knowledge Discovery in Databases: European Conference, (ECML-PKDD), 2021.
    PDF Code

    40. 2020

  40. Active learning for node classification: The additional learning ability from unlabelled nodes
    Juncheng Liu, Yiwei Wang, Bryan Hooi, Renchi Yang, Xiaokui Xiao.
    arXiv preprint arXiv:2012.07065, 2020.
    PDF Code
  41. Graphcrop: Subgraph cropping for graph classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi.
    arXiv preprint arXiv:2009.10564, 2020.
    PDF Code
  42. Learning progressive joint propagation for human motion prediction
    Yujun Cai, Lin Huang, Yiwei Wang, Tat-Jen Cham, Jianfei Cai, Junsong Yuan, Jun Liu, Xu Yang, Yiheng Zhu, Xiaohui Shen, others.
    Computer Vision--ECCV 2020: 16th European Conference, 2020.
    PDF Code
  43. Revisiting convolutional neural networks for urban flow analytics
    Yuxuan Liang, Kun Ouyang, Yiwei Wang, David Samuel Rosenblum.
    Preprint, 2020.
    PDF Code
  44. Detecting implementation bugs in graph convolutional network based node classifiers
    Yiwei Wang, Wei Wang, Yujun Ca, Bryan Hooi, Beng Chin Ooi.
    2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE), 2020.
    PDF Code
  45. KDD
    NodeAug: Semi-supervised node classification with data augmentation
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi.
    Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2020.
    PDF Code
  46. Provably robust node classification via low-pass message passing
    Yiwei Wang, Shenghua Liu, Minji Yoon, Hemank Lamba, Wei Wang, Christos Faloutsos, Bryan Hooi.
    2020 IEEE International Conference on Data Mining (ICDM), 2020.
    PDF Code

    47. 2019

  47. Optimization algorithms for graph Laplacian estimation via ADMM and MM
    Licheng Zhao, Yiwei Wang, Sandeep Kumar, Daniel P Palomar.
    IEEE Transactions on Signal Processing, 2019.
    PDF Code

    48. 2017

  48. Using knowledge graphs to explain entity co-occurrence in Twitter
    Yiwei Wang, Mark James Carman, Yuan-Fang Li.
    Proceedings of the 2017 ACM on Conference on Information and Knowledge Management, 2017.
    PDF Code

Teaching

Services

Area Chair

Conference Reviewer

Journal Reviewer

Contact

Address: 5200 Lake Rd, Merced, CA 95343
Office Location: Science & Engineering 2, Office 205


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