Zobrazeno 1 - 10
of 145
pro vyhledávání: '"Huang, Ruihong"'
Autor:
Lei, Yuanyuan, Huang, Ruihong
Logical fallacy uses invalid or faulty reasoning in the construction of a statement. Despite the prevalence and harmfulness of logical fallacies, detecting and classifying logical fallacies still remains a challenging task. We observe that logical fa
Externí odkaz:
http://arxiv.org/abs/2410.12048
Large Language Models (LLMs) have shown remarkable capabilities in a multitude of Natural Language Processing (NLP) tasks. However, these models are still not immune to limitations such as social biases, especially gender bias. This work investigates
Externí odkaz:
http://arxiv.org/abs/2410.09992
Localizing unusual activities, such as human errors or surveillance incidents, in videos holds practical significance. However, current video understanding models struggle with localizing these unusual events likely because of their insufficient repr
Externí odkaz:
http://arxiv.org/abs/2410.01180
Large Language Models (LLMs) have demonstrated proficiency in a wide array of natural language processing tasks. However, its effectiveness over discourse-level event relation extraction (ERE) tasks remains unexplored. In this paper, we assess the ef
Externí odkaz:
http://arxiv.org/abs/2407.19568
Autor:
Du, Jiangshu, Wang, Yibo, Zhao, Wenting, Deng, Zhongfen, Liu, Shuaiqi, Lou, Renze, Zou, Henry Peng, Venkit, Pranav Narayanan, Zhang, Nan, Srinath, Mukund, Zhang, Haoran Ranran, Gupta, Vipul, Li, Yinghui, Li, Tao, Wang, Fei, Liu, Qin, Liu, Tianlin, Gao, Pengzhi, Xia, Congying, Xing, Chen, Cheng, Jiayang, Wang, Zhaowei, Su, Ying, Shah, Raj Sanjay, Guo, Ruohao, Gu, Jing, Li, Haoran, Wei, Kangda, Wang, Zihao, Cheng, Lu, Ranathunga, Surangika, Fang, Meng, Fu, Jie, Liu, Fei, Huang, Ruihong, Blanco, Eduardo, Cao, Yixin, Zhang, Rui, Yu, Philip S., Yin, Wenpeng
This work is motivated by two key trends. On one hand, large language models (LLMs) have shown remarkable versatility in various generative tasks such as writing, drawing, and question answering, significantly reducing the time required for many rout
Externí odkaz:
http://arxiv.org/abs/2406.16253
Autor:
Jain, Ajit, Kerne, Andruid, Lupfer, Nic, Britain, Gabriel, Perrine, Aaron, Choe, Yoonsuck, Keyser, John, Huang, Ruihong, Seo, Jinsil, Sungkajun, Annie, Lightfoot, Robert, McGuire, Timothy
We investigate how to use AI-based analytics to support design education. The analytics at hand measure multiscale design, that is, students' use of space and scale to visually and conceptually organize their design work. With the goal of making the
Externí odkaz:
http://arxiv.org/abs/2404.05417
Autor:
Lei, Yuanyuan, Huang, Ruihong
Media outlets are becoming more partisan and polarized nowadays. In this paper, we identify media bias at the sentence level, and pinpoint bias sentences that intend to sway readers' opinions. As bias sentences are often expressed in a neutral and fa
Externí odkaz:
http://arxiv.org/abs/2404.01722
Autor:
Lei, Yuanyuan, Miah, Md Messal Monem, Qamar, Ayesha, Reddy, Sai Ramana, Tong, Jonathan, Xu, Haotian, Huang, Ruihong
Most previous research on moral frames has focused on social media short texts, little work has explored moral sentiment within news articles. In news articles, authors often express their opinions or political stance through moral judgment towards e
Externí odkaz:
http://arxiv.org/abs/2404.01715
Opinion summarization is automatically generating summaries from a variety of subjective information, such as product reviews or political opinions. The challenge of opinions summarization lies in presenting divergent or even conflicting opinions. We
Externí odkaz:
http://arxiv.org/abs/2404.01706
Autor:
Liu, Yujian, Zhang, Xinliang Frederick, Zou, Kaijian, Huang, Ruihong, Beauchamp, Nick, Wang, Lu
Public opinion is shaped by the information news media provide, and that information in turn may be shaped by the ideological preferences of media outlets. But while much attention has been devoted to media bias via overt ideological language or topi
Externí odkaz:
http://arxiv.org/abs/2310.18827