Zobrazeno 1 - 10
of 64
pro vyhledávání: '"P. Gopi Krishnan"'
Autor:
Tan, Jingwen, Rajbahadur, Gopi Krishnan, Li, Zi, Song, Xiangfu, Lin, Jianshan, Li, Dan, Zheng, Zibin, Hassan, Ahmed E.
Dataset license compliance is a critical yet complex aspect of developing commercial AI products, particularly with the increasing use of publicly available datasets. Ambiguities in dataset licenses pose significant legal risks, making it challenging
Externí odkaz:
http://arxiv.org/abs/2501.00106
The rapid expansion of foundation models (FMs), such as large language models (LLMs), has given rise to FMware--software systems that integrate FMs as core components. While building demonstration-level FMware is relatively straightforward, transitio
Externí odkaz:
http://arxiv.org/abs/2410.20791
Autor:
Dong, Ximing, Wang, Shaowei, Lin, Dayi, Rajbahadur, Gopi Krishnan, Zhou, Boquan, Liu, Shichao, Hassan, Ahmed E.
Large Language Models excel in tasks like natural language understanding and text generation. Prompt engineering plays a critical role in leveraging LLM effectively. However, LLMs black-box nature hinders its interpretability and effective prompting
Externí odkaz:
http://arxiv.org/abs/2410.13073
Background: Data quality is vital in software analytics, particularly for machine learning (ML) applications like software defect prediction (SDP). Despite the widespread use of ML in software engineering, the effect of data quality antipatterns on t
Externí odkaz:
http://arxiv.org/abs/2408.12560
Bindings for machine learning frameworks (such as TensorFlow and PyTorch) allow developers to integrate a framework's functionality using a programming language different from the framework's default language (usually Python). In this paper, we study
Externí odkaz:
http://arxiv.org/abs/2407.05466
Data clones are defined as multiple copies of the same data among datasets. Presence of data clones between datasets can cause issues such as difficulties in managing data assets and data license violations when using datasets with clones to build AI
Externí odkaz:
http://arxiv.org/abs/2407.12802
Autor:
Hassan, Ahmed E., Lin, Dayi, Rajbahadur, Gopi Krishnan, Gallaba, Keheliya, Cogo, Filipe R., Chen, Boyuan, Zhang, Haoxiang, Thangarajah, Kishanthan, Oliva, Gustavo Ansaldi, Lin, Jiahuei, Abdullah, Wali Mohammad, Jiang, Zhen Ming
Foundation models (FMs), such as Large Language Models (LLMs), have revolutionized software development by enabling new use cases and business models. We refer to software built using FMs as FMware. The unique properties of FMware (e.g., prompts, age
Externí odkaz:
http://arxiv.org/abs/2402.15943
In software engineering, deep learning models are increasingly deployed for critical tasks such as bug detection and code review. However, overfitting remains a challenge that affects the quality, reliability, and trustworthiness of software systems
Externí odkaz:
http://arxiv.org/abs/2401.10359
Autor:
Manu Santhappan Girija, Deepak Menon, Kiran Polavarapu, Veeramani Preethish-Kumar, Seena Vengalil, Saraswati Nashi, Madassu Keertipriya, Mainak Bardhan, Priya Treesa Thomas, Valasani Ravi Kiran, Vikas Nishadham, Arun Sadasivan, Akshata Huddar, Gopi Krishnan Unnikrishnan, Ashita Barthur, Atchayaram Nalini
Publikováno v:
Annals of Indian Academy of Neurology, Vol 27, Iss 5, Pp 552-557 (2024)
Background and Objectives: Cardiovascular magnetic resonance imaging (CMRI) is the noninvasive technique of choice for early detection of cardiac involvement in Duchenne and Becker muscular dystrophy (DMD and BMD, respectively), but is seldom used in
Externí odkaz:
https://doaj.org/article/38c2098435744099ac7e752bf86f779b
Ethereum is one of the most popular platforms for the development of blockchain-powered applications. These applications are known as Dapps. When engineering Dapps, developers need to translate requests captured in the front-end of their application
Externí odkaz:
http://arxiv.org/abs/2206.08959