Filip Naudot

Quantitative-Bipolar-Argumentation

Contributor. Modification to handle sets of contributors, enabling the quantification of multiple arguments collectively contributing to a topic argument.

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lightbench

Maintainer. Developed and currently maintaining the LLM benchmarking framework lightbench, which enables automatic evaluation for code and text generation tasks.

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Performance and Computational Demands of LLMs: Impact of Model Size and Quantization

Naudot, Filip. (2025). In Proceedings of Umeå’s 28th Student Conference in Computing Science (USCCS 2025), edited by Thomas Hellström, Umeå University, Sweden.

Winner – Reinforcement Learning Tournament

Artificial Intelligence - Methods and Applications (Ht24), Umeå University, 2024.