18 citations · 74 across the 22 of their papers we have counts for
4 papers · 1 filter
Eliciting Critical Reasoning in Retrieval-Augmented Language Models via Contrastive Explanations
Leonardo Ranaldi, Marco Valentino, Andrè Freitas
Retrieval-augmented generation (RAG) has emerged as a critical mechanism in contemporary NLP to support Large Language Models(LLMs) in systematically accessing richer factual conte…
Animate, or Inanimate, That is the Question for Large Language Models
Leonardo Ranaldi, Giulia Pucci, Fabio Massimo Zanzotto
The cognitive essence of humans is deeply intertwined with the concept of animacy, which plays an essential role in shaping their memory, vision, and multi-layered language underst…
Self-Refine Instruction-Tuning for Aligning Reasoning in Language Models
Leonardo Ranaldi, Andrè Freitas
The alignments of reasoning abilities between smaller and larger Language Models are largely conducted via Supervised Fine-Tuning (SFT) using demonstrations generated from robust L…
Investigating the Impact of Data Contamination of Large Language Models in Text-to-SQL Translation
Federico Ranaldi, Elena Sofia Ruzzetti, Dario Onorati +5
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…