12 citations · 25 across the 14 of their papers we have counts for
6 papers · 1 filter
Understanding Robustness of Model Editing in Code LLMs
Vinaik Chhetri, Moghis Fereidouni, A. B Siddique +1
Large language models (LLMs) for code are increasingly used in software development, but they remain static after pretraining while APIs and software libraries continue to evolve.…
A Framework for Generating Conversational Recommendation Datasets from Behavioral Interactions
Vinaik Chhetri, Yousaf Reza, Moghis Fereidouni +3
Modern recommendation systems typically follow two complementary paradigms: collaborative filtering, which models long-term user preferences from historical interactions, and conve…
INTERPOS: Interaction Rhythm Guided Positional Morphing for Mobile App Recommender Systems
M. H. Maqbool, Moghis Fereidouni, Umar Farooq +2
The mobile app market has expanded exponentially, offering millions of apps with diverse functionalities, yet research in mobile app recommendation remains limited. Traditional seq…
What Users Value and Critique: Large-Scale Analysis of User Feedback on AI-Powered Mobile Apps
Vinaik Chhetri, Krishna Upadhyay, A. B. Siddique +1
Artificial Intelligence (AI)-powered features have rapidly proliferated across mobile apps in various domains, including productivity, education, entertainment, and creativity. How…
Assessing and Enhancing Quantum Readiness in Mobile Apps
Joseph Strauss, Krishna Upadhyay, A. B. Siddique +2
Quantum computers threaten widely deployed cryptographic primitives such as RSA, DSA, and ECC. While NIST has released post-quantum cryptographic (PQC) standards (e.g., Kyber, Dili…
Analyzing the Evolution and Maintenance of Quantum Software Repositories
Krishna Upadhyay, Vinaik Chhetri, A. B. Siddique +1
Quantum computing is rapidly advancing, but quantum software development faces significant challenges, including a steep learning curve, high hardware error rates, and a lack of ma…