Zobrazeno 1 - 10
of 821 110
pro vyhledávání: '"an exploratory study"'
Gender diversity enhances research by bringing diverse perspectives and innovative approaches. It ensures equitable solutions that address the needs of diverse populations. However, gender disparity persists in research where women remain underrepres
Externí odkaz:
http://arxiv.org/abs/2412.15661
Publikováno v:
Proceedings of the 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE)
This paper explores the integration of Visual Code Assistants in Integrated Development Environments (IDEs). In Software Engineering, whiteboard sketching is often the initial step before coding, serving as a crucial collaboration tool for developers
Externí odkaz:
http://arxiv.org/abs/2412.13386
Autor:
Seshagiri, Vishwanath, Balyan, Siddharth, Anand, Vaastav, Dhole, Kaustubh, Sharma, Ishan, Wildani, Avani, Cambronero, José, Züfle, Andreas
Logging is a critical function in modern distributed applications, but the lack of standardization in log query languages and formats creates significant challenges. Developers currently must write ad hoc queries in platform-specific languages, requi
Externí odkaz:
http://arxiv.org/abs/2412.03612
Autor:
Wang, Yuhang, Sang, Jitao
The o1 system card identifies the o1 models as the most robust within OpenAI, with their defining characteristic being the progression from rapid, intuitive thinking to slower, more deliberate reasoning. This observation motivated us to investigate t
Externí odkaz:
http://arxiv.org/abs/2411.17075
This paper presents a study of participants interacting with and using GaMaDHaNi, a novel hierarchical generative model for Hindustani vocal contours. To explore possible use cases in human-AI interaction, we conducted a user study with three partici
Externí odkaz:
http://arxiv.org/abs/2411.13846
While machine learning (ML) models are becoming mainstream, especially in sensitive application areas, the risk of data leakage has become a growing concern. Attacks like membership inference (MIA) have shown that trained models can reveal sensitive
Externí odkaz:
http://arxiv.org/abs/2411.06613
Statically typed languages offer numerous benefits to developers, such as improved code quality and reduced runtime errors, but they also require the overhead of manual type annotations. To mitigate this burden, language designers have started incorp
Externí odkaz:
http://arxiv.org/abs/2410.23360
Autor:
Kortemeyer, Gerd, Nöhl, Julian
This study explores the use of artificial intelligence in grading high-stakes physics exams, emphasizing the application of psychometric methods, particularly Item Response Theory (IRT), to evaluate the reliability of AI-assisted grading. We examine
Externí odkaz:
http://arxiv.org/abs/2410.19409
Companion robots hold immense potential in providing emotional support to older adults in the rapidly aging world. However, questions have been raised regarding whether having a robotic companion benefits healthy older adults, how they perceive the v
Externí odkaz:
http://arxiv.org/abs/2410.12205
The capabilities of Large Language Models (LLMs) have significantly evolved, extending from natural language processing to complex tasks like code understanding and generation. We expand the scope of LLMs' capabilities to a broader context, using LLM
Externí odkaz:
http://arxiv.org/abs/2410.06667