2 citations · 2 across the 9 of their papers we have counts for
11 papers
The Stochastic Deputy: Structural Tenant Isolation for Tool-Using LLM Agents
Mirza Samad Ahmed Baig, Syeda Anshrah Gillani, Asher Ali +1
Multi-tenant tools commonly accept a tenant identifier and validate it against the caller's entitlement. For a large language model (LLM) agent, that pattern delegates resource sel…
Phase-cycled randomized benchmarking of quantum processors: recovering hidden classical noise correlations
Mirza Samad Ahmed Baig, Syeda Anshrah Gillani, Abdul Akbar Khan +1
Randomized benchmarking can hide classical temporal correlations because its Clifford-twirled response is even in the noise phase. For a stationary symmetric telegraph fluctuator,…
Whose doctor does the AI recommend? An algorithm audit of reputation and demographic signals in large language model-assisted physician choice
Syeda Anshrah Gillani, Mirza Samad Ahmed Baig
Patients increasingly ask large language model (LLM) assistants which doctor to see, making these systems AI infomediaries: algorithms that intermediate one person's choice among o…
How Quantum Is the Advantage? A Fair, Calibration- and Noise-Aware Benchmark and Attribution Audit of Quantum Machine Learning for Network Intrusion Detection
Syeda Anshrah Gillani, Mirza Samad Ahmed Baig, Shahid Munir Shah +2
Quantum machine learning (QML) for network intrusion detection (NIDS) is routinely reported to reach near-perfect accuracy, yet the most rigorous studies find that well-tuned class…
Whose hotel does the AI recommend? An algorithm audit of reputation signals in LLM-assisted hotel selection
Mirza Samad Ahmed Baig, Syeda Anshrah Gillani, Asher Ali
Travelers increasingly ask large language model (LLM) assistants which hotel to book, making these systems gatekeepers of property visibility -- yet what moves their recommendation…
FreqLite: A Lightweight Frequency-Decomposed Linear Model with Adaptive Reversible Normalization for Robust Long-Term Time-Series Forecasting
Mirza Samad Ahmed Baig, Syeda Anshrah Gillani
Long-term time-series forecasting needs models that are accurate yet efficient enough for commodity hardware. Lightweight linear forecasters are remarkably strong in this regime, y…