Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Cheng Ruijia"'
Programmers frequently engage with machine learning tutorials in computational notebooks and have been adopting code generation technologies based on large language models (LLMs). However, they encounter difficulties in understanding and working with
Externí odkaz:
http://arxiv.org/abs/2404.07387
Large language models (LLMs) have the potential to impact a wide range of creative domains, but the application of LLMs to animation is underexplored and presents novel challenges such as how users might effectively describe motion in natural languag
Externí odkaz:
http://arxiv.org/abs/2402.06071
Developers and quality assurance testers often rely on manual testing to test accessibility features throughout the product lifecycle. Unfortunately, manual testing can be tedious, often has an overwhelming scope, and can be difficult to schedule amo
Externí odkaz:
http://arxiv.org/abs/2310.02424
As AI-powered code generation tools such as GitHub Copilot become popular, it is crucial to understand software developers' trust in AI tools -- a key factor for tool adoption and responsible usage. However, we know little about how developers build
Externí odkaz:
http://arxiv.org/abs/2305.11248
Autor:
Tao Yaoding, Zhang Shouyun, Xu Mei, Qin Yuyan, Gao Shang, Wang Tianrui, Li Kaili, Cheng Ruijia, Cao Zhen
Publikováno v:
Green Processing and Synthesis, Vol 13, Iss 1, Pp 53-7 (2024)
Composite coating technology was used to prepare a modified polyamide 6 (PA6) polymer material masterbatch with low mutual interference and good spinnability using molybdenum oxide, tungsten trioxide, graphene oxide, etc., as modifiers. Experiment sh
Externí odkaz:
https://doaj.org/article/9d8b0ca71b22468a99a0f847e39e75ed
While revolutionary AI-powered code generation tools have been rising rapidly, we know little about how and how to help software developers form appropriate trust in those AI tools. Through a two-phase formative study, we investigate how online commu
Externí odkaz:
http://arxiv.org/abs/2212.03491
Autor:
Cheng, Ruijia, Hill, Benjamin Mako
Publikováno v:
Proc. ACM Hum.-Comput. Interact. 6, CSCW2, Article 381 (November 2022), 26 pages
Although informal online learning communities have proliferated over the last two decades, a fundamental question remains: What are the users of these communities expected to learn? Guided by the work of Etienne Wenger on communities of practice, we
Externí odkaz:
http://arxiv.org/abs/2211.04046
Autor:
Cheng, Ruijia, Frens, Jenna
Feedback is a critical piece of the creative process. Prior CSCW research has invented peer-based and crowd-based systems that exchange feedback between online strangers at scale. However, creators run into socio-psychological challenges when engagin
Externí odkaz:
http://arxiv.org/abs/2209.12810
Autor:
Tao Yaoding, Zhang Shouyun, Xu Mei, Shu Qiang, Gao Shang, Liu Yanan, Wang Peisong, Cheng Ruijia
Publikováno v:
e-Polymers, Vol 24, Iss 1, Pp 53-7 (2024)
In this study, we realized a highly luminescent polyester fiber using a special spinneret orifice comprised of eight C-shaped pores and specific process parameters. A moderate amount of reversible photochromism materials was added along with the spec
Externí odkaz:
https://doaj.org/article/0a1b463b699a485cb441793e9785aa36
Automatic text summarization systems commonly involve humans for preparing data or evaluating model performance, yet, there lacks a systematic understanding of humans' roles, experience, and needs when interacting with or being assisted by AI. From a
Externí odkaz:
http://arxiv.org/abs/2206.14863