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cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

Prompting Encoder Models for Zero-Shot Classification: A Cross-Domain Study in Italian

Serena Auriemma, Martina Miliani, Mauro Madeddu +3

Addressing the challenge of limited annotated data in specialized fields and low-resource languages is crucial for the effective use of Language Models (LMs). While most Large Lang…