Evalita-LLM: Benchmarking Large Language Models on Italian

• URL: http://arxiv.org/abs/2502.02289v1
• Date: Tue, 04 Feb 2025 12:58:19 GMT
• Title: Evalita-LLM: Benchmarking Large Language Models on Italian
• Authors: Bernardo Magnini, Roberto Zanoli, Michele Resta, Martin Cimmino, Paolo Albano, Marco Madeddu, Viviana Patti,
• Abstract summary: Evalita-LLM is a benchmark designed to evaluate Large Language Models (LLMs) on Italian tasks. All tasks are native Italian, avoiding issues of translating from Italian and potential cultural biases. The benchmark includes generative tasks, enabling more natural interaction with LLMs.
• Score: 3.3334839725239798
• License:
• Abstract: We describe Evalita-LLM, a new benchmark designed to evaluate Large Language Models (LLMs) on Italian tasks. The distinguishing and innovative features of Evalita-LLM are the following: (i) all tasks are native Italian, avoiding issues of translating from Italian and potential cultural biases; (ii) in addition to well established multiple-choice tasks, the benchmark includes generative tasks, enabling more natural interaction with LLMs; (iii) all tasks are evaluated against multiple prompts, this way mitigating the model sensitivity to specific prompts and allowing a fairer and objective evaluation. We propose an iterative methodology, where candidate tasks and candidate prompts are validated against a set of LLMs used for development. We report experimental results from the benchmark's development phase, and provide performance statistics for several state-of-the-art LLMs.

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