← Search

Dario Onorati

2 accepted papers

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 12SourcePDFScholar
2023

Measuring bias in Instruction-Following models with P-AT

EMNLP 2023long findings

Instruction-Following Language Models (IFLMs) are promising and versatile tools for solving many downstream, information-seeking tasks. Given their success, there is an urgent need to have a shared resource to determine whether existing and new IFLMs are prone to produce biased language interactions…

Cited by 7SourceScholar