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Minghao Shao
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2020 – today
- 2024
- [c4]Hu Zhang, Huifeng Liu, Youli Zhang, Ying Guo, Hongjun Dai, Minghao Shao, Hongyu Xu:
Energy Consumption Prediction Method for Refrigeration Systems Based on Adversarial Networks and Transformer Networks. KSEM (5) 2024: 305-315 - [i5]Minghao Shao, Boyuan Chen, Sofija Jancheska, Brendan Dolan-Gavitt, Siddharth Garg, Ramesh Karri, Muhammad Shafique:
An Empirical Evaluation of LLMs for Solving Offensive Security Challenges. CoRR abs/2402.11814 (2024) - [i4]Kaichen Huang, Hai-Hang Sun, Shenghua Wan, Minghao Shao, Shuai Feng, Le Gan, De-Chuan Zhan:
DIDA: Denoised Imitation Learning based on Domain Adaptation. CoRR abs/2404.03382 (2024) - [i3]Kaichen Huang, Minghao Shao, Shenghua Wan, Hai-Hang Sun, Shuai Feng, Le Gan, De-Chuan Zhan:
SENSOR: Imitate Third-Person Expert's Behaviors via Active Sensoring. CoRR abs/2404.03386 (2024) - [i2]Minghao Shao, Sofija Jancheska, Meet Udeshi, Brendan Dolan-Gavitt, Haoran Xi, Kimberly Milner, Boyuan Chen, Max Yin, Siddharth Garg, Prashanth Krishnamurthy, Farshad Khorrami, Ramesh Karri, Muhammad Shafique:
NYU CTF Dataset: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security. CoRR abs/2406.05590 (2024) - 2023
- [c3]Shenghua Wan, Yucen Wang, Minghao Shao, Ruying Chen, De-Chuan Zhan:
SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models. ICML 2023: 35426-35443 - [i1]Shenghua Wan, Yucen Wang, Minghao Shao, Ruying Chen, De-Chuan Zhan:
SeMAIL: Eliminating Distractors in Visual Imitation via Separated Models. CoRR abs/2306.10695 (2023) - 2022
- [c2]Gang Wang, Xingxing Ke, Jian Hu, Qianling Li, Minghao Shao, Jianfeng Fan:
Learning to Prune: General and Efficient Approximate Nearest Neighbor Search with Direction Navigating Graph. DSDE 2022: 50-58 - 2021
- [c1]Xiaoyue Zhao, Minghao Shao, Houfang Liu, Ruiting Zhao, Xichen Sun, Xiao Liu, Xiaoming Wu, Yi Yang, Tianling Ren:
Large Coercive Field in Hf0.5Zr0.5O2-based Capacitors with Gd Top Electrode. ASICON 2021: 1-4
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last updated on 2024-08-10 00:31 CEST by the dblp team
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