activity
20182026
most citedT5APR: Empowering Automated Program Repair across Languages through Checkpoint Ensemble

11 citations · 16 across the 7 of their papers we have counts for

collaborators

8 papers

cs.SI2026

A Novel Gravity-Quasi-Laplacian Approach to Identifying Influential Nodes in Complex Networks

Shima Esfandiari, Seyed Mostafa Fakhrahmad

Identifying influential nodes in complex networks is a fundamental challenge with broad applications in areas such as social network analysis, communication infrastructure, transpo…

cs.SI2026

Uncertainty-Aware Fuzzy Centrality Measures for Influential Node Identification: A Structural Modeling Approach Toward E-Commerce Applications

Shima Esfandiari, Seyed Mostafa Fakhrahmad

In recent years, e-commerce platforms have become one of the most prominent examples of large-scale interaction networks, where understanding influence dynamics among users, produc…

cs.SE2025

MultiMend: Multilingual Program Repair with Context Augmentation and Multi-Hunk Patch Generation

Reza Gharibi, Mohammad Hadi Sadreddini, Seyed Mostafa Fakhrahmad

Debugging software remains a labor-intensive and time-consuming process despite advances in testing and verification. Learning-based automated program repair (APR) has shown promis…

cs.SI2024★ 4 cited

Mining Influential Spreaders in Complex Networks by an Effective Combination of the Degree and K-Shell

Shima Esfandiari, Seyed Mostafa Fakhrahmad

Graph mining is an important technique that used in many applications such as predicting and understanding behaviors and information dissemination within networks. One crucial aspe…

cs.CL2024★ 1 cited

Towards Efficient Patient Recruitment for Clinical Trials: Application of a Prompt-Based Learning Model

Mojdeh Rahmanian, Seyed Mostafa Fakhrahmad, Seyedeh Zahra Mousavi

Objective: Clinical trials are essential for advancing pharmaceutical interventions, but they face a bottleneck in selecting eligible participants. Although leveraging electronic h…

cs.CL2024

Estimating the severity of dental and oral problems via sentiment classification over clinical reports

Sare Mahdavifar, Seyed Mostafa Fakhrahmad, Elham Ansarifard

Analyzing authors' sentiments in texts as a technique for identifying text polarity can be practical and useful in various fields, including medicine and dentistry. Currently, due…