Recruiting

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

Development Roadmap

Student Track Starting Point Stage 1 (3-6 months) Stage 2 (3-6 months) Stage 3 (3-6 months) Final Outcome
Research Interns Zero AI background student First AI Top Conference submission First AI Top Conference Publication PhD or Industry Researcher Offer Career Launch
Student Track Starting Point Stage 1 (6-12 months) Stage 2 (12-36 months) Stage 3 (6-12 months) Final Outcome
PhD Students Junior Researcher First Publication and Industry Intern Sufficient AI Publications Graduation with Academic or Industry Researcher Offer Career Success

🎯 100% Research Resource Coverage Guarantee

All students across all tracks receive full access to computational resources and AI model APIs

Student Track Independent & Sufficient GPU Resources (A100, H100, H200, A6000) OpenAI LLM APIs Credits Fast APIs for Many Other (Multimodal) LLMs (Deepseek, Claude, Llama, Qwen) Weekly One-to-One Meeting Real-time Responses on Wechat
Research Interns ✅ ✅ ✅ ✅ ✅
PhD Students ✅ ✅ ✅ ✅ ✅

Research Focus

My research focuses on large foundation models based trustworthy natural language processing and its applications as AI assistants. Our research considers not only textual but also vision data, with the target of understanding ubiquitos multi-modal data in real-world applications.

Selected Publications [Google Scholar][DBLP]

    2025

  1. 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.
    Transactions on Machine Learning Research (TMLR), 2025.
    PDF Code
  2. ACL
    Context-DPO: Aligning Language Models for Context-Faithfulness
    Baolong Bi, Shaohan Huang, Yiwei Wang, Tianchi Yang, Zihan Zhang, Haizhen Huang, Lingrui Mei, Junfeng Fang, Zehao Li, Furu Wei, Weiwei Deng, Feng Sun, Qi Zhang, Shenghua Liu.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  3. Decoding by Contrasting Knowledge: Enhancing Large Language Model Confidence on Edited Facts
    Baolong Bi, Shenghua Liu, Lingrui Mei, Yiwei Wang, Junfeng Fang, Pengliang Ji, Xueqi Cheng.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  4. 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.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  5. DRS: Deep Question Reformulation With Structured Output
    Zhecheng Li, Yiwei Wang, Bryan Hooi, Yujun Cai, Nanyun Peng, Kai-Wei Chang.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  6. METAL: A Multi-Agent Framework for Chart Generation with Test-Time Scaling
    Bingxuan Li, Yiwei Wang, Jiuxiang Gu, Kai-Wei Chang, Nanyun Peng.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  7. Vulnerability of LLMs to Vertically Aligned Text Manipulations
    Zhecheng Li, Yiwei Wang, Bryan Hooi, Yujun Cai, Zhen Xiong, Nanyun Peng, Kai-Wei Chang.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  8. EvoStealer: Differential Evolution for Prompt Template Stealing Against Text-to-Image Synthesis
    Yurong Wu, Fangwen Mu, Qiuhong Zhang, Jinjing Zhao, Xinrun Xu, Lingrui Mei, Yang Wu, Lin Shi, Junjie Wang, Zhiming Ding, Yiwei Wang.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  9. Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering
    Rongzhi Zhu, Xiangyu Liu, Zequn Sun, Yiwei Wang, Wei Hu.
    Association for Computational Linguistics ACL, 2025.
    PDF Code
  10. Peripheral Memory for LLMs: Integration of Sequential Memory Banks with Adaptive Querying
    Songlin Zhai, Yuan Meng, Yongrui Chen, Yiwei Wang, Guilin Qi.
    International Conference on Machine Learning (ICML), 2025.
    PDF Code
  11. ICLR
    Is Factuality Enhancement a Free Lunch For LLMs? Better Factuality Can Lead to Worse Context-Faithfulness
    Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Xueqi Cheng.
    The Thirteenth International Conference on Learning Representations (ICLR), 2025.
    PDF Code
  12. ICLR
    OptiBench meets ReSocratic: Measure and improve LLMs for optimization modeling
    Zhicheng Yang, Yiwei Wang, Yinya Huang, Zhijiang Guo, Wei Shi, Xiongwei Han, Liang Feng, Linqi Song, Xiaodan Liang, Jing Tang.
    The Thirteenth International Conference on Learning Representations (ICLR), 2025.
    PDF Code
  13. ICLR
    MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced With Reliable Evaluations
    Shaochen Zhong, others.
    The Thirteenth International Conference on Learning Representations (ICLR), 2025.
    PDF Code
  14. NAACL
    Tricking Retrievers with Influential Tokens: An Efficient Black-Box Corpus Poisoning Attack
    Chen Wang, Yiwei Wang, Yujun Cai, Bryan Hooi.
    Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025.
    PDF Code
  15. NAACL
    Vulnerability of Large Language Models to Output Prefix Jailbreaks: Impact of Positions on Safety
    Yiwei Wang, Muhao Chen, Nanyun Peng, Kai-Wei Chang.
    Proceedings of the 2025 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2025.
    PDF Code
  16. 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
  17. Preprint
    Are LLMs Really Not Knowledgable? Mining the Submerged Knowledge in LLMs' Memory
    Xingjian Tao, Yiwei Wang, Yujun Cai, Zhicheng Yang, Jing Tang.
    arXiv preprint arXiv:2412.20846, 2025.
    PDF Code
  18. 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

    19. 2024

  19. 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
  20. 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
  21. 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
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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

    29. 2023

  29. 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
  30. 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
  31. 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
  32. 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
  33. 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

    34. 2022

  34. 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
  35. 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
  36. 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
  37. 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
  38. 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
  39. 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

    40. 2021

  40. 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
  41. 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
  42. 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
  43. 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
  44. 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
  45. 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
  46. Modeling Trajectories with Neural Ordinary Differential Equations.
    Yuxuan Liang, Kun Ouyang, Hanshu Yan, Yiwei Wang, Zekun Tong, Roger Zimmermann.
    IJCAI, 2021.
    PDF Code
  47. 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
  48. 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
  49. 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
  50. 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

    51. 2020

  51. 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
  52. Graphcrop: Subgraph cropping for graph classification
    Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Bryan Hooi.
    arXiv preprint arXiv:2009.10564, 2020.
    PDF Code
  53. 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
  54. Revisiting convolutional neural networks for urban flow analytics
    Yuxuan Liang, Kun Ouyang, Yiwei Wang, David Samuel Rosenblum.
    Preprint, 2020.
    PDF Code
  55. 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
  56. 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
  57. 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

    58. 2019

  58. 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

    59. 2017

  59. 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

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