1 citations · 2 across the 6 of their papers we have counts for
6 papers
Peerify: Benchmarking Peer-Review Claim Verification
Alireza Daghighfarsoodeh, Sajad Ebrahimi, Ali Ghorbanpour +4
Peer review plays a central role in scholarly publishing, yet verifying whether reviewer claims are supported by manuscript evidence remains a largely manual and time-consuming pro…
Peerispect: Claim Verification in Scientific Peer Reviews
Ali Ghorbanpour, Soroush Sadeghian, Alireza Daghighfarsoodeh +4
Peer review is central to scientific publishing, yet reviewers frequently include claims that are subjective, rhetorical, or misaligned with the submitted work. Assessing whether r…
Consistency Meets Verification: Enhancing Test Generation Quality in Large Language Models Without Ground-Truth Solutions
Hamed Taherkhani, Alireza DaghighFarsoodeh, Mohammad Chowdhury +2
Large Language Models (LLMs) have significantly advanced automated test generation, yet existing methods often rely on ground-truth code for verification, risking bug propagation a…
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…
Task-oriented Prompt Enhancement via Script Generation
Chung-Yu Wang, Alireza DaghighFarsoodeh, Hung Viet Pham
Large Language Models (LLMs) have demonstrated remarkable abilities across various tasks, leveraging advanced reasoning. Yet, they struggle with task-oriented prompts due to a lack…
Selection of Prompt Engineering Techniques for Code Generation through Predicting Code Complexity
Chung-Yu Wang, Alireza DaghighFarsoodeh, Hung Viet Pham
Large Language Models (LLMs) have demonstrated impressive performance in software engineering tasks. However, improving their accuracy in generating correct and reliable code remai…