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pro vyhledávání: '"Qu, Huamin"'
Large Language Models (LLMs) have gained significant attention but also raised concerns due to the risk of misuse. Jailbreak prompts, a popular type of adversarial attack towards LLMs, have appeared and constantly evolved to breach the safety protoco
Externí odkaz:
http://arxiv.org/abs/2407.03045
Exploratory visual data analysis tools empower data analysts to efficiently and intuitively explore data insights throughout the entire analysis cycle. However, the gap between common programmatic analysis (e.g., within computational notebooks) and e
Externí odkaz:
http://arxiv.org/abs/2406.11637
Large language models (LLMs) have exhibited impressive abilities for multimodal content comprehension and reasoning with proper prompting in zero- or few-shot settings. Despite the proliferation of interactive systems developed to support prompt engi
Externí odkaz:
http://arxiv.org/abs/2406.03843
Autor:
Li, Haobo, Kam-Kwai, Wong, Luo, Yan, Chen, Juntong, Liu, Chengzhong, Zhang, Yaxuan, Lau, Alexis Kai Hon, Qu, Huamin, Liu, Dongyu
The escalating frequency and intensity of heat-related climate events, particularly heatwaves, emphasize the pressing need for advanced heat risk management strategies. Current approaches, primarily relying on numerical models, face challenges in spa
Externí odkaz:
http://arxiv.org/abs/2406.03317
Text animation serves as an expressive medium, transforming static communication into dynamic experiences by infusing words with motion to evoke emotions, emphasize meanings, and construct compelling narratives. Crafting animations that are semantica
Externí odkaz:
http://arxiv.org/abs/2404.11614
Computational notebooks are widely utilized for exploration and analysis. However, creating slides to communicate analysis results from these notebooks is quite tedious and time-consuming. Researchers have proposed automatic systems for generating sl
Externí odkaz:
http://arxiv.org/abs/2403.09121
Autor:
Feng, Zezheng, Jiang, Yifan, Wang, Hongjun, Fan, Zipei, Ma, Yuxin, Yang, Shuang-Hua, Qu, Huamin, Song, Xuan
Recent achievements in deep learning (DL) have shown its potential for predicting traffic flows. Such predictions are beneficial for understanding the situation and making decisions in traffic control. However, most state-of-the-art DL models are con
Externí odkaz:
http://arxiv.org/abs/2403.04812
Autor:
Feng, Zezheng, Zhu, Fang, Wang, Hongjun, Hao, Jianing, Yang, ShuangHua, Zeng, Wei, Qu, Huamin
Higher-order patterns reveal sequential multistep state transitions, which are usually superior to origin-destination analysis, which depicts only first-order geospatial movement patterns. Conventional methods for higher-order movement modeling first
Externí odkaz:
http://arxiv.org/abs/2403.03822
Financial cluster analysis allows investors to discover investment alternatives and avoid undertaking excessive risks. However, this analytical task faces substantial challenges arising from many pairwise comparisons, the dynamic correlations across
Externí odkaz:
http://arxiv.org/abs/2402.08978
Autor:
Jin, Xiaofu, Tong, Wai, Wei, Xiaoying, Wang, Xian, Kuang, Emily, Mo, Xiaoyu, Qu, Huamin, Fan, Mingming
The global aging trend compels older adults to navigate the evolving digital landscape, presenting a substantial challenge in mastering smartphone applications. While Augmented Reality (AR) holds promise for enhancing learning and user experience, it
Externí odkaz:
http://arxiv.org/abs/2402.04991