12 citations · 33 across the 11 of their papers we have counts for
11 papers
Design Proteins Using Large Language Models: Enhancements and Comparative Analyses
Kamyar Zeinalipour, Neda Jamshidi, Monica Bianchini +2
Pre-trained LLMs have demonstrated substantial capabilities across a range of conventional natural language processing (NLP) tasks, such as summarization and entity recognition. In…
Show Less, Instruct More: Enriching Prompts with Definitions and Guidelines for Zero-Shot NER
Andrew Zamai, Andrea Zugarini, Leonardo Rigutini +2
Recently, several specialized instruction-tuned Large Language Models (LLMs) for Named Entity Recognition (NER) have emerged. Compared to traditional NER approaches, these models h…
Automating Turkish Educational Quiz Generation Using Large Language Models
Kamyar Zeinalipour, Yusuf Gökberk Keptiğ, Marco Maggini +1
Crafting quizzes from educational content is a pivotal activity that benefits both teachers and students by reinforcing learning and evaluating understanding. In this study, we int…
Clue-Instruct: Text-Based Clue Generation for Educational Crossword Puzzles
Andrea Zugarini, Kamyar Zeinalipour, Surya Sai Kadali +3
Crossword puzzles are popular linguistic games often used as tools to engage students in learning. Educational crosswords are characterized by less cryptic and more factual clues t…
Multitask Kernel-based Learning with Logic Constraints
Michelangelo Diligenti, Marco Gori, Marco Maggini +1
This paper presents a general framework to integrate prior knowledge in the form of logic constraints among a set of task functions into kernel machines. The logic propositions pro…
Neural paraphrasing by automatically crawled and aligned sentence pairs
Achille Globo, Antonio Trevisi, Andrea Zugarini +3
Paraphrasing is the task of re-writing an input text using other words, without altering the meaning of the original content. Conversational systems can exploit automatic paraphras…