Zobrazeno 1 - 10
of 7 351
pro vyhledávání: '"Hassan, Ahmed"'
Foundation models (FM), such as large language models (LLMs), which are large-scale machine learning (ML) models, have demonstrated remarkable adaptability in various downstream software engineering (SE) tasks, such as code completion, code understan
Externí odkaz:
http://arxiv.org/abs/2407.04065
Predicting potential long-time contributors (LTCs) early allows project maintainers to effectively allocate resources and mentoring to enhance their development and retention. Mapping programming language expertise to developers and characterizing pr
Externí odkaz:
http://arxiv.org/abs/2405.13852
A long continuous integration (CI) build forces developers to wait for CI feedback before starting subsequent development activities, leading to time wasted. In addition to a variety of build scheduling and test selection heuristics studied in the pa
Externí odkaz:
http://arxiv.org/abs/2405.00796
Autor:
Hassan, Ahmed
Microporous carbonates host a significant portion of the remaining oil-in-place in the giant carbonate reservoirs of the Middle East. Improved understanding of petrophysical and multi-phase flow properties at the pore-scale is essential for the devel
Externí odkaz:
http://hdl.handle.net/10754/673896
Autor:
Hassan, Ahmed
Autismus-Spektrum-Störung (ASD) ist eine neurologische Entwicklungsstörung, die durch eine Reihe von Entwicklungsstörungen gekennzeichnet ist, die zu einem Mangel an sozialen, kommunikativen und kooperativen Fähigkeiten führen. Sozio-kommunikati
Externí odkaz:
http://edoc.hu-berlin.de/18452/28710
Autor:
Hassan, Ahmed
This thesis makes a novel contribution to the state-of-the-art literature on EHD melting enhancement of PCMs showing the effects of electroconvection flow and solid extraction during the melting process. The details of the contribution made by this w
Externí odkaz:
http://hdl.handle.net/11375/29374
Large Language Models (LLMs) have significantly advanced natural language processing (NLP) tasks but also pose ethical and societal risks due to their propensity to generate harmful content. To address this, various approaches have been developed to
Externí odkaz:
http://arxiv.org/abs/2404.19048
The advent of Foundation Models (FMs) and AI-powered copilots has transformed the landscape of software development, offering unprecedented code completion capabilities and enhancing developer productivity. However, the current task-driven nature of
Externí odkaz:
http://arxiv.org/abs/2404.10225
This paper investigates the complexities of integrating Large Language Models (LLMs) into software products, with a focus on the challenges encountered for determining their readiness for release. Our systematic review of grey literature identifies c
Externí odkaz:
http://arxiv.org/abs/2403.18958
Deciding what combination of operators to use across the Edge AI tiers to achieve specific latency and model performance requirements is an open question for MLOps engineers. This study aims to empirically assess the accuracy vs inference time trade-
Externí odkaz:
http://arxiv.org/abs/2403.17154