1 citations · 1 across the 2 of their papers we have counts for
3 papers
RGFL: Reasoning Guided Fault Localization for Automated Program Repair Using Large Language Models
Melika Sepidband, Hamed Taherkhani, Hung Viet Pham +1
Fault Localization (FL) is a critical step in Automated Program Repair (APR), and its importance has increased with the rise of Large Language Model (LLM)-based repair agents. In r…
Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach
Melika Sepidband, Hamed Taherkhani, Song Wang +1
Automatic code generation has gained significant momentum with the advent of Large Language Models (LLMs) such as GPT-4. Although many studies focus on improving the effectiveness…
Deep-Bench: Deep Learning Benchmark Dataset for Code Generation
Alireza Daghighfarsoodeh, Chung-Yu Wang, Hamed Taherkhani +4
Deep learning (DL) has revolutionized areas such as computer vision, natural language processing, and more. However, developing DL systems is challenging due to the complexity of D…