1 citations · 1 across the 3 of their papers we have counts for
4 papers
Inference-Time Vulnerability Beyond Shallow Safety: Alignment Along Generation Trajectories
Kyungmin Park, Taesup Kim
Safety-aligned Large Language Models (LLMs) remain vulnerable to interventions during inference that redirect generation toward harmful outputs. Recent work attributes this to shal…
DGNNFlow: A Streaming Dataflow Architecture for Real-Time Edge-based Dynamic GNN Inference in HL-LHC Trigger Systems
Davendra Maharaj, Tu Pham, Peter Meiring +4
Dynamic GNN inference exhibits strong capability to model interactions over time, such as complex particle collision events in High Energy Physics (HEP) experiments at High Luminos…
Anomaly Detection Based on Machine Learning for the CMS Electromagnetic Calorimeter Online Data Quality Monitoring
Abhirami Harilal, Kyungmin Park, Manfred Paulini
A real-time autoencoder-based anomaly detection system using semi-supervised machine learning has been developed for the online Data Quality Monitoring system of the electromagneti…
Autoencoder-based Online Data Quality Monitoring for the CMS Electromagnetic Calorimeter
Abhirami Harilal, Kyungmin Park, Michael Andrews +1
The online Data Quality Monitoring system (DQM) of the CMS electromagnetic calorimeter (ECAL) is a crucial operational tool that allows ECAL experts to quickly identify, localize,…