1 citations · 1 across the 3 of their papers we have counts for
5 papers
From Training Exposure to Membership Evidence: A Controlled Study of OLMo 2
Ali Banaei, Muhammad Shahab Shahzad, Gerald Q. Maguire +2
Whether a language model was trained on a document matters for copyright, privacy, and benchmark contamination. Yet most membership-inference (MI) evaluations on language models co…
Dissecting GPU Utilization for LLM Inference on Nvidia Hopper
Mohammad Siavashi, Gerald Q. Maguire, Dejan Kostic +1
A single SM utilization percentage can make an LLM inference workload look compute-saturated while hiding how much useful work is being done. The problem is not that the counter is…
Blink: CPU-Free LLM Inference by Delegating the Serving Stack to GPU and SmartNIC
Mohammad Siavashi, Mariano Scazzariello, Gerald Q. Maguire +2
Large Language Model (LLM) inference is rapidly becoming a core datacenter service, yet current serving stacks keep the host CPU on the critical path for orchestration and token-le…
KVComm: Enabling Efficient LLM Communication through Selective KV Sharing
Xiangyu Shi, Marco Chiesa, Gerald Q. Maguire +1
Large Language Models (LLMs) are increasingly deployed in multi-agent systems, where effective inter-model communication is crucial. Existing communication protocols either rely on…
FMM-Head: Enhancing Autoencoder-based ECG anomaly detection with prior knowledge
Giacomo Verardo, Magnus Boman, Samuel Bruchfeld +4
Detecting anomalies in electrocardiogram data is crucial to identifying deviations from normal heartbeat patterns and providing timely intervention to at-risk patients. Various Aut…