4 papers
ExpliCa: Evaluating Explicit Causal Reasoning in Large Language Models
Martina Miliani, Serena Auriemma, Alessandro Bondielli +4
Large Language Models (LLMs) are increasingly used in tasks requiring interpretive and inferential accuracy. In this paper, we introduce ExpliCa, a new dataset for evaluating LLMs…
CLASS-IT: Conversational and Lecture-Aligned Small-Scale Instruction Tuning for BabyLMs
Luca Capone, Alessandro Bondielli, Alessandro Lenci
This work investigates whether small-scale LMs can benefit from instruction tuning. We compare conversational and question-answering instruction tuning datasets, applied either in…
All-in-one: Understanding and Generation in Multimodal Reasoning with the MAIA Benchmark
Davide Testa, Giovanni Bonetta, Raffaella Bernardi +5
We introduce MAIA (Multimodal AI Assessment), a native-Italian benchmark designed for fine-grained investigation of the reasoning abilities of visual language models on videos. MAI…
BAMBI: Developing Baby Language Models for Italian
Alice Suozzi, Luca Capone, Gianluca E. Lebani +1
This paper presents BAMBI (BAby language Models Boostrapped for Italian), a series of Baby Language Models (BabyLMs) trained on data that mimic the linguistic input received by a f…