2 citations · 4 across the 8 of their papers we have counts for
8 papers
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…
CASTILLO: Characterizing Response Length Distributions of Large Language Models
Daniel F. Perez-Ramirez, Dejan Kostic, Magnus Boman
Efficiently managing compute resources for Large Language Model (LLM) inference remains challenging due to the inherently stochastic and variable lengths of autoregressive text gen…
Priority-Aware Preemptive Scheduling for Mixed-Priority Workloads in MoE Inference
Mohammad Siavashi, Faezeh Keshmiri Dindarloo, Dejan Kostic +1
Large Language Models have revolutionized natural language processing, yet serving them efficiently in data centers remains challenging due to mixed workloads comprising latency-se…
Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues
Daniele Cipollone, Changjie Wang, Mariano Scazzariello +4
In today's digital landscape, the importance of timely and accurate vulnerability detection has significantly increased. This paper presents a novel approach that leverages transfo…
Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning
Laura Puccioni, Alireza Farshin, Mariano Scazzariello +3
Large Language Models (LLMs) have demonstrated their exceptional performance in various complex code generation tasks. However, their broader adoption is limited by significant com…
Robust Generalization of Graph Neural Networks for Carrier Scheduling
Daniel F. Perez-Ramirez, Carlos Pérez-Penichet, Nicolas Tsiftes +3
Battery-free sensor tags are devices that leverage backscatter techniques to communicate with standard IoT devices, thereby augmenting a network's sensing capabilities in a scalabl…
Just-in-Time Packet State Prefetching
Hamid Ghasemirahni, Alireza Farshin, Dejan Kostic +1
Could information about future incoming packets be used to build more efficient CPU-based packet processors? Can such information be obtained accurately? This paper studies novel p…
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…