collaborators

5 papers

cs.LG2026

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…

cs.CL2025

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…

cs.LG2025

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…

cs.SE2025

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…

cs.LG2025

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…