| On the Convergence of FedAvg on Non-IID Data X Li*, K Huang*, W Yang*, S Wang, Z Zhang arXiv preprint arXiv:1907.02189, 2019 | 2766 | 2019 |
| Visual adversarial examples jailbreak aligned large language models X Qi*, K Huang*, A Panda, P Henderson, M Wang, P Mittal Proceedings of the AAAI Conference on Artificial Intelligence 38 (19), 21527 …, 2024 | 208* | 2024 |
| Score approximation, estimation and distribution recovery of diffusion models on low-dimensional data M Chen*, K Huang*, T Zhao, M Wang International Conference on Machine Learning, 4672-4712, 2023 | 122 | 2023 |
| Why Do Deep Residual Networks Generalize Better than Deep Feedforward Networks?---A Neural Tangent Kernel Perspective K Huang*, Y Wang*, M Tao, T Zhao Advances in neural information processing systems 33, 2698-2709, 2020 | 112 | 2020 |
| Fast federated learning in the presence of arbitrary device unavailability X Gu*, K Huang*, J Zhang, L Huang Advances in Neural Information Processing Systems 34, 12052-12064, 2021 | 106 | 2021 |
| Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications B Wei*, K Huang*, Y Huang*, T Xie, X Qi, M Xia, P Mittal, M Wang, ... arXiv preprint arXiv:2402.05162, 2024 | 72 | 2024 |
| A 5′ UTR language model for decoding untranslated regions of mRNA and function predictions Y Chu, D Yu, Y Li, K Huang, Y Shen, L Cong, J Zhang, M Wang Nature Machine Intelligence, 1-12, 2024 | 46 | 2024 |
| Reward-directed conditional diffusion: Provable distribution estimation and reward improvement H Yuan, K Huang, C Ni, M Chen, M Wang Advances in Neural Information Processing Systems 36, 2024 | 38* | 2024 |
| SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal Behaviors T Xie, X Qi, Y Zeng, Y Huang, UM Sehwag, K Huang, L He, B Wei, D Li, ... arXiv preprint arXiv:2406.14598, 2024 | 31 | 2024 |
| Embodied LLM Agents Learn to Cooperate in Organized Teams X Guo, K Huang, J Liu, W Fan, N Vélez, Q Wu, H Wang, TL Griffiths, ... arXiv preprint arXiv:2403.12482, 2024 | 28 | 2024 |
| CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments K Huang*, Y Qu*, H Cousins, WA Johnson, D Yin, M Shah, D Zhou, ... arXiv preprint arXiv:2404.18021, 2024 | 21 | 2024 |
| Optimal gradient-based algorithms for non-concave bandit optimization B Huang, K Huang, S Kakade, JD Lee, Q Lei, R Wang, J Yang Advances in Neural Information Processing Systems 34, 29101-29115, 2021 | 17 | 2021 |
| Deep Reinforcement Learning for Cost-Effective Medical Diagnosis Z Yu*, Y Li*, J Kim*, K Huang*, Y Luo, M Wang arXiv preprint arXiv:2302.10261, 2023 | 14 | 2023 |
| AI Risk Management Should Incorporate Both Safety and Security X Qi, Y Huang, Y Zeng, E Debenedetti, J Geiping, L He, K Huang, ... arXiv preprint arXiv:2405.19524, 2024 | 13 | 2024 |
| Going beyond linear rl: Sample efficient neural function approximation B Huang, K Huang, S Kakade, JD Lee, Q Lei, R Wang, J Yang Advances in Neural Information Processing Systems 34, 8968-8983, 2021 | 10 | 2021 |
| SpecDec++: Boosting Speculative Decoding via Adaptive Candidate Lengths K Huang, X Guo, M Wang arXiv preprint arXiv:2405.19715, 2024 | 8* | 2024 |
| A Short Note on the Relationship of Information Gain and Eluder Dimension K Huang, SM Kakade, JD Lee, Q Lei arXiv preprint arXiv:2107.02377, 2021 | 8 | 2021 |
| TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling J Qiu, Y Lu, Y Zeng, J Guo, J Geng, H Wang, K Huang, Y Wu, M Wang arXiv preprint arXiv:2410.16033, 2024 | 6 | 2024 |
| Scaling In-Context Demonstrations with Structured Attention T Cai*, K Huang*, JD Lee, M Wang arXiv preprint arXiv:2307.02690, 2023 | 3 | 2023 |
| A Theoretical Perspective for Speculative Decoding Algorithm M Yin, M Chen, K Huang, M Wang arXiv preprint arXiv:2411.00841, 2024 | 2 | 2024 |
Mengdi WangCenter for Statistics & Machine Learning, ECE, Princeton UniversityDirección de correo verificada de princeton.edu