Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Alipour, Mohammad Amin"'
Autor:
Karanjai, Rabimba, Hussain, Aftab, Rabin, Md Rafiqul Islam, Xu, Lei, Shi, Weidong, Alipour, Mohammad Amin
Unit testing is crucial in software engineering for ensuring quality. However, it's not widely used in parallel and high-performance computing software, particularly scientific applications, due to their smaller, diverse user base and complex logic.
Externí odkaz:
http://arxiv.org/abs/2407.05202
Autor:
Amoozadeh, Matin, Nam, Daye, Prol, Daniel, Alfageeh, Ali, Prather, James, Hilton, Michael, Ragavan, Sruti Srinivasa, Alipour, Mohammad Amin
The new capabilities of generative artificial intelligence tools Generative AI, such as ChatGPT, allow users to interact with the system in intuitive ways, such as simple conversations, and receive (mostly) good-quality answers. These systems can sup
Externí odkaz:
http://arxiv.org/abs/2407.00305
Information Foraging Theory's (IFT) framing of human information seeking choices as decision-theoretic cost-value judgments has successfully explained how people seek information among linked patches of information (e.g., linked webpages). However, t
Externí odkaz:
http://arxiv.org/abs/2406.04452
Large language models (LLMs) have revolutionized software development practices, yet concerns about their safety have arisen, particularly regarding hidden backdoors, aka trojans. Backdoor attacks involve the insertion of triggers into training data,
Externí odkaz:
http://arxiv.org/abs/2405.11466
Autor:
Hussain, Aftab, Rabin, Md Rafiqul Islam, Ahmed, Toufique, Xu, Bowen, Devanbu, Premkumar, Alipour, Mohammad Amin
Large language models (LLMs) have provided a lot of exciting new capabilities in software development. However, the opaque nature of these models makes them difficult to reason about and inspect. Their opacity gives rise to potential security risks,
Externí odkaz:
http://arxiv.org/abs/2405.02828
Trojan signatures, as described by Fields et al. (2021), are noticeable differences in the distribution of the trojaned class parameters (weights) and the non-trojaned class parameters of the trojaned model, that can be used to detect the trojaned mo
Externí odkaz:
http://arxiv.org/abs/2402.16896
Large language models (LLMs) have revolutionized software development practices, yet concerns about their safety have arisen, particularly regarding hidden backdoors, aka trojans. Backdoor attacks involve the insertion of triggers into training data,
Externí odkaz:
http://arxiv.org/abs/2402.12936
Large language models (LLMs) are becoming an integrated part of software development. These models are trained on large datasets for code, where it is hard to verify each data point. Therefore, a potential attack surface can be to inject poisonous da
Externí odkaz:
http://arxiv.org/abs/2312.04004
With the rapid growth of research in trojaning deep neural models of source code, we observe that there is a need of developing a benchmark trojaned models for testing various trojan detection and unlearning techniques. In this work, we aim to provid
Externí odkaz:
http://arxiv.org/abs/2311.14850
Autor:
Amoozadeh, Matin, Daniels, David, Nam, Daye, Kumar, Aayush, Chen, Stella, Hilton, Michael, Ragavan, Sruti Srinivasa, Alipour, Mohammad Amin
Generative artificial systems (GenAI) have experienced exponential growth in the past couple of years. These systems offer exciting capabilities, such as generating programs, that students can well utilize for their learning. Among many dimensions th
Externí odkaz:
http://arxiv.org/abs/2310.04631