5 papers
Asm2SrcEval: Evaluating Large Language Models for Assembly-to-Source Code Translation
Parisa Hamedi, Hamed Jelodar, Samita Bai +3
Assembly-to-source code translation is a critical task in reverse engineering, cybersecurity, and software maintenance, yet systematic benchmarks for evaluating large language mode…
SBAN: A Framework & Multi-Dimensional Dataset for Large Language Model Pre-Training and Software Code Mining
Hamed Jelodar, Mohammad Meymani, Samita Bai +2
This paper introduces SBAN (Source code, Binary, Assembly, and Natural Language Description), a large-scale, multi-dimensional dataset designed to advance the pre-training and eval…
XGen-Q: An Explainable Domain-Adaptive LLM Framework with Retrieval-Augmented Generation for Software Security
Hamed Jelodar, Mohammad Meymani, Roozbeh Razavi-Far +1
Generative AI and large language models (LLMs) have shown strong capabilities in code understanding, but their use in cybersecurity, particularly for malware detection and analysis…
NLD-LLM: A systematic framework for evaluating small language transformer models on natural language description
Hamed Jelodar, Mohammad Meymani, Parisa Hamedi +4
Natural Language Description (NLD) is a Natural Language Processing (NLP) task that requires models to generate structured and meaningful outputs from natural language inputs. In t…
Large Language Models (LLMs) for Source Code Analysis: applications, models and datasets
Hamed Jelodar, Mohammad Meymani, Roozbeh Razavi-Far
Large language models (LLMs) and transformer-based architectures are increasingly utilized for source code analysis. As software systems grow in complexity, integrating LLMs into c…