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Andrea Favalli

2 accepted papers

2025

Position Paper: MeMo: Towards Language Models with Associative Memory Mechanisms

ACL 2025finding

Memorization is a fundamental ability of Transformer-based Large Language Models, achieved through learning. In this position/theory paper, we propose a paradigm shift by designing an architecture to memorize text directly, bearing in mind the principle that memorization precedes learning. We introd…

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2024

Investigating the Impact of Data Contamination of Large Language Models in Text-to-SQL translation

ACL 2024findings

Understanding textual description to generate code seems to be an achieved capability of instruction-following Large Language Models (LLMs) in zero-shot scenario. However, there is a severe possibility that this translation ability may be influenced by having seen target textual descriptions and the…

Cited by 12Source ↗PDF ↗Scholar ↗