| An efficiency-boosting client selection scheme for federated learning with fairness guarantee T Huang, W Lin, W Wu, L He, K Li, AY Zomaya IEEE Transactions on Parallel and Distributed Systems 32 (7), 1552-1564, 2020 | 343 | 2020 |
| Stochastic client selection for federated learning with volatile clients T Huang, W Lin, L Shen, K Li, AY Zomaya IEEE Internet of Things Journal 9 (20), 20055-20070, 2022 | 166 | 2022 |
| An ant colony optimization-based multiobjective service replicas placement strategy for fog computing T Huang, W Lin, C Xiong, R Pan, J Huang IEEE Transactions on Cybernetics 51 (11), 5595-5608, 2020 | 120 | 2020 |
| A survey on large language model-based game agents S Hu, T Huang, G Liu, RR Kompella, F Ilhan, SF Tekin, Y Xu, Z Yahn, ... arXiv preprint arXiv:2404.02039, 2024 | 116 | 2024 |
| Large Language Model-Powered Smart Contract Vulnerability Detection: New Perspectives S Hu, T Huang, F İlhan, SF Tekin, L Liu IEEE Trust, Privacy and Security 2023, 2023 | 112 | 2023 |
| Vaccine: Perturbation-aware alignment for large language models against harmful fine-tuning attack T Huang, S Hu, L Liu NeurIPS2024, 2024 | 103* | 2024 |
| Fedspeed: Larger local interval, less communication round, and higher generalization accuracy Y Sun, L Shen, T Huang, L Ding, D Tao ICLR 2023, 2023 | 87 | 2023 |
| Harmful fine-tuning attacks and defenses for large language models: A survey T Huang, S Hu, F Ilhan, SF Tekin, L Liu arXiv preprint arXiv:2409.18169, 2024 | 76 | 2024 |
| Lisa: Lazy Safety Alignment for Large Language Models against Harmful Fine-tuning Attack T Huang, S Hu, F Ilhan, SF Tekin, L Liu NeurIPS2024, 2024 | 72* | 2024 |
| Booster: Tackling harmful fine-tuning for large language models via attenuating harmful perturbation T Huang, S Hu, F Ilhan, SF Tekin, L Liu ICLR2025, 2024 | 58 | 2024 |
| Achieving personalized federated learning with sparse local models T Huang, S Liu, L Shen, F He, W Lin, D Tao arXiv preprint arXiv:2201.11380, 2022 | 48 | 2022 |
| Antidote: Post-fine-tuning safety alignment for large language models against harmful fine-tuning T Huang, G Bhattacharya, P Joshi, J Kimball, L Liu ICML2025, 2024 | 45* | 2024 |
| Safety tax: Safety alignment makes your large reasoning models less reasonable T Huang, S Hu, F Ilhan, SF Tekin, Z Yahn, Y Xu, L Liu arXiv preprint arXiv:2503.00555, 2025 | 42 | 2025 |
| Pokéllmon: A human-parity agent for pokémon battles with large language models S Hu, T Huang, L Liu arXiv preprint arXiv:2402.01118, 2024 | 39 | 2024 |
| Zipzap: Efficient training of language models for large-scale fraud detection on blockchain S Hu, T Huang, KH Chow, W Wei, Y Wu, L Liu Proceedings of the ACM Web Conference 2024, 2807-2816, 2024 | 38 | 2024 |
| Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training T Huang, S Hu, KH Chow, F Ilhan, S Tekin, L Liu NeurIPS2023, 2023 | 37 | 2023 |
| Probe before you talk: Towards black-box defense against backdoor unalignment for large language models B Yi, T Huang, S Chen, T Li, Z Liu, Z Chu, Y Li ICLR2025, 2025 | 35 | 2025 |
| LLM-TOPLA: Efficient LLM Ensemble by Maximising Diversity S Furkan Tekin, F Ilhan, T Huang, S Hu, L Liu arXiv e-prints, arXiv: 2410.03953, 2024 | 34* | 2024 |
| Targeted vaccine: Safety alignment for large language models against harmful fine-tuning via layer-wise perturbation G Liu, W Lin, Q Mu, T Huang, R Mo, Y Tao, L Shen IEEE Transactions on Information Forensics and Security, 2025 | 26 | 2025 |
| Adaptive deep neural network inference optimization with eenet F Ilhan, KH Chow, S Hu, T Huang, S Tekin, W Wei, Y Wu, M Lee, ... Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2024 | 25 | 2024 |
Ling LiuGeorgia Institute of TechnologyVerified email at cc.gatech.edu
