8 citations · 13 across the 11 of their papers we have counts for
12 papers
GAPS: Dimension-Level Gates for Conditional Activation Steering
Moghis Fereidouni, Muhammad Umair Haider, Hassan Sajjad +1
Activation steering suppresses undesired behaviors in language models by adding a steering vector to the hidden state during generation. Recent conditional methods such as CAST and…
Security and Privacy Taxonomy Generation from Mobile App Reviews
Moghis Fereidouni, Vinaik Chhetri, Umar Farooq +1
Mobile app reviews are a rich, continuously renewing source of how users experience privacy and security, yet existing taxonomies of these concerns are hand-crafted and cannot keep…
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.…
Evaluating Sparse Autoencoders for Monosemantic Representation
Moghis Fereidouni, Muhammad Umair Haider, Peizhong Ju +1
A key barrier to interpreting large language models is polysemanticity, where neurons activate for multiple unrelated concepts. Sparse autoencoders (SAEs) have been proposed to mit…
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…