Talk at NVidia
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Marco Chiesa presented the recent results from the CoNEXT paper at NVidia Research.
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NetConfEval accepted at CoNEXT 2024
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Can Large Language Models facilitate network configuration? In our recently accepted CoNEXT 2024 paper, we investigate the opportunities and challenges in operating network systems using recent LLM models.
We devise a benchmark for evaluating the capabilities of different LLM models on a variety of networking tasks and show different ways of integrating such models within existing systems. Our results show that different models works better in different tasks. Translating high-level human-language requirements into formal specifications (e.g., API function calling) can be done with small models. However, generating code that controls network systems is only doable with larger LLMs, such as GPT4.
This is a first fundamental first step in our SEMLA project looking at ways to integrate LLMs into system development.
GitHub code: link
Hugging Face: link
Paper PDF: link
Two master theses in progress
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Two exceptional students have been hired through a selective process within the SEMLA process: Laura Puccioni and Daniele Cipollone. Laura is working on understanding how to compress models for code generation while Daniele is focusing on detecting vulnerabilities using LLMs. We look forward to seeing the outcome of the two theses!
Talk at 5G Italy
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We presented results from the SEMLA project both in a presentation and as part of a panel discussion within the 5G Italy event in Rome (https://www.5gitaly.eu/). Many interesting discussions and follow-ups!
Talk at Global Connect
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We presented parts of the current results from the SEMLA project both in a presentation and as part of a panel discussion within the Global Connect event in Paris. Many interesting discussions and follow-ups!
