| Can Language Models Solve Graph Problems in Natural Language? H Wang, S Feng, T He, Z Tan, X Han, Y Tsvetkov NeurIPS 2023, spotlight, 2023 | 125 | 2023 |
| TwiBot-22: Towards graph-based Twitter bot detection S Feng, Z Tan, H Wan, N Wang, Z Chen, B Zhang, Q Zheng, W Zhang, ... NeurIPS 2022, Dataset and Benchmark Track, 2022 | 92 | 2022 |
| Heterogeneity-aware twitter bot detection with relational graph transformers S Feng, Z Tan, R Li, M Luo AAAI 2022, 2022 | 79 | 2022 |
| Towards Safer Large Language Models through Machine Unlearning Z Liu, G Dou, Z Tan, Y Tian, M Jiang ACL 2024, findings, 2024 | 44 | 2024 |
| KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion Z Tan, Z Chen, S Feng, Q Zhang, Q Zheng, J Li, M Luo The Web Conference 2023, 2022 | 34 | 2022 |
| Democratizing large language models via personalized parameter-efficient fine-tuning Z Tan, Q Zeng, Y Tian, Z Liu, B Yin, M Jiang EMNLP 2024, 2024 | 23 | 2024 |
| BotPercent: Estimating Bot Populations in Twitter Communities Z Tan, S Feng, M Sclar, H Wan, M Luo, Y Choi, Y Tsvetkov EMNLP 2023, findings, 2023 | 23* | 2023 |
| BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts Y Liu, Z Tan, H Wang, S Feng, Q Zheng, M Luo SIGIR 2023, 2023 | 21 | 2023 |
| DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection H Wan, S Feng, Z Tan, H Wang, Y Tsvetkov, M Luo ACL 2024, findings, 2024 | 18 | 2024 |
| Hofa: Twitter bot detection with homophily-oriented augmentation and frequency adaptive attention S Ye, Z Tan, Z Lei, R He, H Wang, Q Zheng, M Luo arXiv preprint arXiv:2306.12870, 2023 | 12 | 2023 |
| PAR: Political Actor Representation Learning with Social Context and Expert Knowledge S Feng, Z Tan, Z Chen, N Wang, P Yu, Q Zheng, X Chang, M Luo EMNLP 2022, 2022 | 12 | 2022 |
| KALM: Knowledge-Aware Integration of Local, Document, and Global Contexts for Long Document Understanding S Feng, Z Tan, W Zhang, Z Lei, Y Tsvetkov ACL 2023, 2022 | 12 | 2022 |
| User Modeling in the Era of Large Language Models: Current Research and Future Directions Z Tan, M Jiang IEEE Data Engineering Bulletin (DEBULL) 2023., 2023 | 11 | 2023 |
| Knowledge crosswords: Geometric reasoning over structured knowledge with large language models W Ding, S Feng, Y Liu, Z Tan, V Balachandran, T He, Y Tsvetkov ACL 2024, findings, 2023 | 10 | 2023 |
| Machine unlearning in generative ai: A survey Z Liu, G Dou, Z Tan, Y Tian, M Jiang arXiv preprint arXiv:2407.20516, 2024 | 8 | 2024 |
| Empirical guidelines for deploying llms onto resource-constrained edge devices R Qin, D Liu, C Xu, Z Yan, Z Tan, Z Jia, A Nassereldine, J Li, M Jiang, ... arXiv preprint arXiv:2406.03777, 2024 | 8 | 2024 |
| LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection Z Cai, Z Tan, Z Lei, H Wang, Z Zhu, Q Zheng, M Luo WSDM 2024, 2023 | 8 | 2023 |
| Large Language Models Can Self-Correct with Key Condition Verification Z Wu, Q Zeng, Z Zhang, Z Tan, C Shen, M Jiang Proceedings of the 2024 Conference on Empirical Methods in Natural Language …, 2024 | 5* | 2024 |
| What Does the Bot Say? Opportunities and Risks of Large Language Models in Social Media Bot Detection S Feng, H Wan, N Wang, Z Tan, M Luo, Y Tsvetkov ACL 2024, 2024 | 5 | 2024 |
| AHEAD: A Triple Attention Based Heterogeneous Graph Anomaly Detection Approach S Yang, B Zhang, S Feng, Z Tan, Q Zheng, J Zhou, M Luo CIAC 2023, 2022 | 5 | 2022 |
Shangbin FengUniversity of WashingtonVerified email at cs.washington.edu
