10 citations · 10 across the 3 of their papers we have counts for
3 papers
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…
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…
Making Network Configuration Human Friendly
Changjie Wang, Mariano Scazzariello, Alireza Farshin +2
This paper explores opportunities to utilize Large Language Models (LLMs) to make network configuration human-friendly, simplifying the configuration of network devices and minimiz…