most citedAI-based Question Answering Assistance for Analyzing Natural-language Requirements

2 citations · 6 across the 5 of their papers we have counts for

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5 papers

cs.SE20232 cited

Hyperbolic Code Retrieval: A Novel Approach for Efficient Code Search Using Hyperbolic Space Embeddings

Xunzhu Tang, zhenghan Chen, Saad Ezzini +4

Within the realm of advanced code retrieval, existing methods have primarily relied on intricate matching and attention-based mechanisms. However, these methods often lead to compu…

cs.SE20232 cited

Multilevel Semantic Embedding of Software Patches: A Fine-to-Coarse Grained Approach Towards Security Patch Detection

Xunzhu Tang, zhenghan Chen, Saad Ezzini +4

The growth of open-source software has increased the risk of hidden vulnerabilities that can affect downstream software applications. This concern is further exacerbated by softwar…

cs.SE2023

Learning to Represent Patches

Xunzhu Tang, Haoye Tian, Zhenghan Chen +6

Patch representation is crucial in automating various software engineering tasks, like determining patch accuracy or summarizing code changes. While recent research has employed de…

cs.CL2023

Letz Translate: Low-Resource Machine Translation for Luxembourgish

Yewei Song, Saad Ezzini, Jacques Klein +3

Natural language processing of Low-Resource Languages (LRL) is often challenged by the lack of data. Therefore, achieving accurate machine translation (MT) in a low-resource enviro…

cs.SE20232 cited

AI-based Question Answering Assistance for Analyzing Natural-language Requirements

Saad Ezzini, Sallam Abualhaija, Chetan Arora +1

By virtue of being prevalently written in natural language (NL), requirements are prone to various defects, e.g., inconsistency and incompleteness. As such, requirements are freque…