1 citations · 1 across the 2 of their papers we have counts for
3 papers
Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark
Hamed Taherkhani, Mohammad Abdollahi, Melika Sepidband +3
Large language models (LLMs) are increasingly used in coding tasks, but their ability to reason about code execution remains unclear. Existing repository-level QA benchmarks mainly…
Demystifying Errors in LLM Reasoning Traces: An Empirical Study of Code Execution Simulation
Mohammad Abdollahi, Khandaker Rifah Tasnia, Soumit Kanti Saha +3
Understanding a program's runtime reasoning behavior, meaning how intermediate states and control flows lead to final execution results, is essential for reliable code generation,…
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…