collaborators

11 papers

cs.CV2026

SPARC: Subspace Position-Aware Robust Few-Shot Calibration for Distribution-Shifted Industrial Anomaly Detection

Seokhee Han, Seungjun Chu, Mateusz Nowak +1

Vision-based industrial anomaly detectors are calibrated on one distribution but may be deployed on another that differs in illumination, fixture placement, or sensor characteristi…

cs.LG2026

RADAR: Relative Angular Divergence Across Representations

Xavier Cadet, Mateusz Nowak, Peter Chin

Machine learning methods rely on data. However, gathering suitable data can be challenging due to availability constraints, cost, or the need for domain expertise. Expanding datase…

cs.CR2026

Retrieval-Augmented LLMs for Security Incident Analysis

Xavier Cadet, Aditya Vikram Singh, Harsh Mamania +6

Investigating cybersecurity incidents requires collecting and analyzing evidence from multiple log sources, including intrusion detection alerts, network traffic records, and authe…

quant-ph2026

Hermitian Matrix Function Synthesis without Block-Encoding

Anuradha Mahasinghe, Kaushika De Silva, Xavier Cadet +3

Implementing polynomial functions of Hermitian matrices on quantum hardware is a foundational task in quantum computing, critical for accurate Hamiltonian simulation, quantum linea…

cs.LG2026

WARP: Weight Teleportation for Attack-Resilient Unlearning Protocols

Mohammad M Maheri, Xavier Cadet, Peter Chin +1

Approximate machine unlearning aims to efficiently remove the influence of specific data points from a trained model, offering a practical alternative to full retraining. However,…

cs.CL2026

ABCD: All Biases Come Disguised

Mateusz Nowak, Xavier Cadet, Peter Chin

Multiple-choice question (MCQ) benchmarks have been a standard evaluation practice for measuring LLMs' ability to reason and answer knowledge-based questions. Through a synthetic N…