collaborators

11 papers

cs.SI2026

From Propagation to Protection: Risk-Aware Diffusion for Harm Minimization in Signed Social Networks

Aaqib Zahoor, Janibul Bashir, Iqra Altaf Gillani

Real-world social relationships are not uniformly supportive. Information through hostile connections can increase resistance, anxiety, or misinformation rather than adoption. Clas…

cs.CL2026

Repair, Not Improvement: Decomposing Constrained Decoding in Tool-Call Abstention

Janghoon Lee

Function calling is what the recent accounting of constrained generation explicitly sets aside: it finds the decoder's contribution small for format constraints, then warns in its…

cs.LG2026

ATR-Bench: A Federated Learning Benchmark for Adaptation, Trust, and Reasoning

Tajamul Ashraf, Mohammed Mohsen Peerzada, Moloud Abdar +5

Federated Learning (FL) has emerged as a promising paradigm for collaborative model training while preserving data privacy across decentralized participants. As FL adoption grows,…

cs.CL2026

Bolbosh: Script-Aware Flow Matching for Kashmiri Text-to-Speech

Tajamul Ashraf, Burhaan Rasheed Zargar, Saeed Abdul Muizz +5

Kashmiri is spoken by around 7 million people but remains critically underserved in speech technology, despite its official status and rich linguistic heritage. The lack of robust…

cs.DC2025

Highly Dynamic and Fully Distributed Data Structures

John Augustine, Antonio Cruciani, Iqra Altaf Gillani

We study robust and efficient distributed algorithms for building and maintaining distributed data structures in dynamic Peer-to-Peer (P2P) networks. P2P networks are characterized…

cs.CV2025

Generalizable Federated Learning using Client Adaptive Focal Modulation

Tajamul Ashraf, Iqra Altaf Gillani

Federated learning (FL) has proven essential for privacy-preserving, collaborative training across distributed clients. Our prior work, TransFed, introduced a robust transformer-ba…