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20232026
most citedMultitask Kernel-based Learning with Logic Constraints

12 citations · 56 across the 16 of their papers we have counts for

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cs.CL2026

Multilingual Training and Evaluation Resources for Vision-Language Models

Daniela Baiamonte, Elena Fano, Matteo Gabburo +3

Vision Language Models (VLMs) achieved rapid progress in the recent years. However, despite their growth, VLMs development is heavily grounded on English, leading to two main limit…

cs.CL2024

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…

cs.CL2024★ 2 cited

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…

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024

Enhancing Modern Supervised Word Sense Disambiguation Models by Semantic Lexical Resources

Stefano Melacci, Achille Globo, Leonardo Rigutini

Supervised models for Word Sense Disambiguation (WSD) currently yield to state-of-the-art results in the most popular benchmarks. Despite the recent introduction of Word Embeddings…

cs.CL2024★ 1 cited

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…

cs.CL2024★ 10 cited

Fast Vocabulary Transfer for Language Model Compression

Leonidas Gee, Andrea Zugarini, Leonardo Rigutini +1

Real-world business applications require a trade-off between language model performance and size. We propose a new method for model compression that relies on vocabulary transfer.…

cs.CL2024★ 3 cited

BUSTER: a "BUSiness Transaction Entity Recognition" dataset

Andrea Zugarini, Andrew Zamai, Marco Ernandes +1

Albeit Natural Language Processing has seen major breakthroughs in the last few years, transferring such advances into real-world business cases can be challenging. One of the reas…

cs.CL2024★ 2 cited

Multi-word Tokenization for Sequence Compression

Leonidas Gee, Leonardo Rigutini, Marco Ernandes +1

Large Language Models have proven highly successful at modelling a variety of tasks. However, this comes at a steep computational cost that hinders wider industrial uptake. In this…

cs.CL2023★ 1 cited

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…

cs.CL2023★ 2 cited

An energy-based comparative analysis of common approaches to text classification in the Legal domain

Sinan Gultekin, Achille Globo, Andrea Zugarini +2

Most Machine Learning research evaluates the best solutions in terms of performance. However, in the race for the best performing model, many important aspects are often overlooked…