12 citations · 19 across the 14 of their papers we have counts for
14 papers
TalkFa: A Unified Benchmark for Farsi Dialogue Generation and Understanding
Neda Jamshidi, Kamyar Zeinalipour, Fahimeh Akbari +3
Farsi, spoken by more than 120 million people, lacks a comprehensive benchmark for dialogue generation and understanding. We introduce TALKFA, a unified benchmark comprising three…
From Arabic Text to Puzzles: LLM-Driven Development of Arabic Educational Crosswords
Kamyar Zeinalipour, Mohamed Zaky Saad, Marco Maggini +1
We present an Arabic crossword puzzle generator from a given text that utilizes advanced language models such as GPT-4-Turbo, GPT-3.5-Turbo and Llama3-8B-Instruct, specifically dev…
Advancing Student Writing Through Automated Syntax Feedback
Kamyar Zeinalipour, Mehak Mehak, Fatemeh Parsamotamed +2
This study underscores the pivotal role of syntax feedback in augmenting the syntactic proficiency of students. Recognizing the challenges faced by learners in mastering syntactic…
Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases
Christian Di Maio, Cristian Cosci, Marco Maggini +2
The growing ubiquity of Retrieval-Augmented Generation (RAG) systems in several real-world services triggers severe concerns about their security. A RAG system improves the generat…
Harnessing LLMs for Educational Content-Driven Italian Crossword Generation
Kamyar Zeinalipour, Achille Fusco, Asya Zanollo +2
In this work, we unveil a novel tool for generating Italian crossword puzzles from text, utilizing advanced language models such as GPT-4o, Mistral-7B-Instruct-v0.3, and Llama3-8b-…
SLIMER-IT: Zero-Shot NER on Italian Language
Andrew Zamai, Leonardo Rigutini, Marco Maggini +1
Traditional approaches to Named Entity Recognition (NER) frame the task into a BIO sequence labeling problem. Although these systems often excel in the downstream task at hand, the…
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…
A Turkish Educational Crossword Puzzle Generator
Kamyar Zeinalipour, Yusuf Gökberk Keptiğ, Marco Maggini +2
This paper introduces the first Turkish crossword puzzle generator designed to leverage the capabilities of large language models (LLMs) for educational purposes. In this work, we…
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…
ArabIcros: AI-Powered Arabic Crossword Puzzle Generation for Educational Applications
Kamyar Zeinalipour, Mohamed Zaky Saad, Marco Maggini +1
This paper presents the first Arabic crossword puzzle generator driven by advanced AI technology. Leveraging cutting-edge large language models including GPT4, GPT3-Davinci, GPT3-C…
Italian Crossword Generator: Enhancing Education through Interactive Word Puzzles
Kamyar Zeinalipour, Tommaso laquinta, Asya Zanollo +4
Educational crosswords offer numerous benefits for students, including increased engagement, improved understanding, critical thinking, and memory retention. Creating high-quality…
SortNet: Learning To Rank By a Neural-Based Sorting Algorithm
Leonardo Rigutini, Tiziano Papini, Marco Maggini +1
The problem of relevance ranking consists of sorting a set of objects with respect to a given criterion. Since users may prefer different relevance criteria, the ranking algorithms…