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2023. Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions. X Hu, X Li, J Chen, Y Li, Y Li, X Li, Y Wang, Q Liu, L Wen, PS Yu, Z Guo. arXiv preprint...
Xiaochuan Li's Homepage. Hi! I am a third-year undergraduate at School of Software, Tsinghua University. My research interests lie in Machine Learning and Natural Language Processing, with a specific focus on Large Language Models.
Code. Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.
Dec 12, 2023 · Image Content Generation with Causal Reasoning. Xiaochuan Li, Baoyu Fan, Runze Zhang, Liang Jin, Di Wang, Zhenhua Guo, Yaqian Zhao, Rengang Li. The emergence of ChatGPT has once again sparked research in generative artificial intelligence (GAI).
Xiaochuan Li is one of the most recognized jazz trumpet player and composer in China. Li is the Winner of best jazz album of the 1st CMA music awards; he is also the Winner of Best Instrumental Album and Best Studio-Recording Album of the 1st JZ Awards.
View Xiaochuan (Stephanie) Li’s profile on LinkedIn, a professional community of 1 billion members. Ph.D. candidate in statistics at the University of Georgia; Internship at LinkedIn as an…
- Wells Fargo
Xiaochuan Li received the master’s degree in 2019 and is a Senior Researcher with Inspur Electronic Information Industry Co., Ltd. From 2019 to 2022, he worked on person detection and object tracking, when he joined the Inspur's multimodal intelligence project for video analysis and retrieval, and led the development and evaluation of multi ...
Xiaochuan Li. Affiliation. School of Automation, Beijing University of Posts and Telecommunications No. 10, Xitucheng Road, Haidian District, Beijing, China. Publication Topics.
Semantic Scholar profile for Xiaochuan Li, with 7 highly influential citations and 39 scientific research papers.
Sep 9, 2020 · In this study, a three-step remaining service life (RSL) prediction method, which involves feature extraction, feature selection, and fusion and prognostics, is proposed for large-scale rotating machinery in the presence of scarce failure data.
