1 citations · 1 across the 6 of their papers we have counts for
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Likelihood Ranking doesn't Scale Like Prompting in LLMs
Alessandro Bondielli, Lucia Passaro, Davide Bacciu +1
LLM evaluation is commonly performed either by prompting models to produce answers or by scoring candidate outputs with likelihood-based metrics. In multiple-choice QA, however, st…
Parts-of-Speech as Emergent Categories in SAE Latent Space
Alessandro Bondielli, Lucia Passaro, Serena Auriemma +1
Sparse AutoEncoders (SAEs) offer a promising way to inspect language model representations, but it is still unclear what kind of linguistic structure their latents expose. We use p…
An Experimental Comparison of the Most Popular Approaches to Fake News Detection
Pietro Dell'Oglio, Alessandro Bondielli, Francesco Marcelloni +1
In recent years, fake news detection has received increasing attention in public debate and scientific research. Despite advances in detection techniques, the production and spread…
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…
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…
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…