Zobrazeno 1 - 10
of 5 831
pro vyhledávání: '"Lu, Chang"'
Autor:
He, Jianfeng, Yang, Runing, Yu, Linlin, Li, Changbin, Jia, Ruoxi, Chen, Feng, Jin, Ming, Lu, Chang-Tien
Text summarization, a key natural language generation (NLG) task, is vital in various domains. However, the high cost of inaccurate summaries in risk-critical applications, particularly those involving human-in-the-loop decision-making, raises concer
Externí odkaz:
http://arxiv.org/abs/2406.17274
Autor:
Beigi, Mohammad, Shen, Ying, Yang, Runing, Lin, Zihao, Wang, Qifan, Mohan, Ankith, He, Jianfeng, Jin, Ming, Lu, Chang-Tien, Huang, Lifu
Despite their vast capabilities, Large Language Models (LLMs) often struggle with generating reliable outputs, frequently producing high-confidence inaccuracies known as hallucinations. Addressing this challenge, our research introduces InternalInspe
Externí odkaz:
http://arxiv.org/abs/2406.12053
Autor:
Wang, Linhan, Cheng, Kai, Lei, Shuo, Wang, Shengkun, Yin, Wei, Lei, Chenyang, Long, Xiaoxiao, Lu, Chang-Tien
We present DC-Gaussian, a new method for generating novel views from in-vehicle dash cam videos. While neural rendering techniques have made significant strides in driving scenarios, existing methods are primarily designed for videos collected by aut
Externí odkaz:
http://arxiv.org/abs/2405.17705
Network interdiction problems are combinatorial optimization problems involving two players: one aims to solve an optimization problem on a network, while the other seeks to modify the network to thwart the first player's objectives. Such problems ty
Externí odkaz:
http://arxiv.org/abs/2405.16409
Autor:
Wang, Zaitian, Wang, Pengfei, Liu, Kunpeng, Wang, Pengyang, Fu, Yanjie, Lu, Chang-Tien, Aggarwal, Charu C., Pei, Jian, Zhou, Yuanchun
Data augmentation is a series of techniques that generate high-quality artificial data by manipulating existing data samples. By leveraging data augmentation techniques, AI models can achieve significantly improved applicability in tasks involving sc
Externí odkaz:
http://arxiv.org/abs/2405.09591
Exploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challenges
Recent advancements in Large Language Models (LLMs) have enabled the creation of fake news, particularly in complex fields like healthcare. Studies highlight the gap in the deceptive power of LLM-generated fake news with and without human assistance,
Externí odkaz:
http://arxiv.org/abs/2403.18249
The fairness and trustworthiness of Large Language Models (LLMs) are receiving increasing attention. Implicit hate speech, which employs indirect language to convey hateful intentions, occupies a significant portion of practice. However, the extent t
Externí odkaz:
http://arxiv.org/abs/2402.11406
Autor:
Hu, Hao-Chun, Chang, Shyue-Yih, Wang, Chuen-Heng, Li, Kai-Jun, Cho, Hsiao-Yun, Chen, Yi-Ting, Lu, Chang-Jung, Tsai, Tzu-Pei, Lee, Oscar Kuang-Sheng
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 6, p e25247 (2021)
BackgroundDysphonia influences the quality of life by interfering with communication. However, a laryngoscopic examination is expensive and not readily accessible in primary care units. Experienced laryngologists are required to achieve an accurate d
Externí odkaz:
https://doaj.org/article/e5c00ea4b4c54dc280949a2b2f838d45
The meaning of complex phrases in natural language is composed of their individual components. The task of compositional generalization evaluates a model's ability to understand new combinations of components. Previous studies trained smaller, task-s
Externí odkaz:
http://arxiv.org/abs/2312.07763
Predicting stock market is vital for investors and policymakers, acting as a barometer of the economic health. We leverage social media data, a potent source of public sentiment, in tandem with macroeconomic indicators as government-compiled statisti
Externí odkaz:
http://arxiv.org/abs/2312.03758