vol. 10, n. 2
pp. 146
ISBN pdf 9791255001430
The rapid advancement of Large Language Models (LLMs) has revolutionized the field of Natural Language Processing (NLP) and Artificial Intelligence (AI) in recent years.
Transformer-based models such as GPT-3 and BERT have demonstrated remarkable capabilities in modeling and generating human-like text. These models have not only redefined the potential of AI systems but also revolutionized applications across a broad spectrum, including machine translation, sentiment analysis, question answering, and beyond. While the era of LLMs has significantly expanded the horizons of AI, it has also presented critical challenges in effectively and responsibly harnessing their capabilities.
This special issue was conceived as a dedicated platform for exploring the latest advancements, methodologies, and applications of LLMs. It sought to foster collaboration and knowledge exchange within the NLP and AI communities, encouraging researchers and practitioners to address real-world challenges while also delving into the theoretical foundations of language in machine learning. The issue builds on discussions initiated at the NL4AI 2023 workshop held at AIxIA 2023 (Bassignana et al. 2023), where many contributions showcased the innovative use of LLMs for natural language understanding and generation tasks.
Dominique Brunato, Istituto di Linguistica Computazionale “Antonio Zampolli”, CNR
Marco Polignano, Università di Bari Aldo Moro
Alan Ramponi, Fondazione Bruno Kessler
Introduction to the Special Issue on Natural Language for Artificial Intelligence in the Era of LLMs
Elisa Bassignana, Dominique Brunato, Marco Polignano, Alan Ramponi
Evaluation of event plausibility recognition in Large (Vision)-Language Models
Maria Cassese, Alessandro Bondielli, Alessandro Lenci
One Picture and One Thousand Words: Toward integrated multimodal
generative models
Roberto Zamparelli
Yet another approximation of human semantic judgments using LLMs... but with quantized local models on novel data
Andrea Amelio Ravelli, Marianna Marcella Bolognesi
Large Language Models for Detecting Bias in Job Descriptions
Tristan Everitt, Paul Ryan, Brian Davis, Kolawole J. Adebayo
Unipa-GPT: Large Language Models for university-oriented QA in Italian
Irene Siragusa, Roberto Pirrone
BERTinchamps: Cost-Effective In-House Training of Language Models in
French
Amaury Fierens, Sébastien Jodogne
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Bassignana - Brunato - Polignano et al., Introduction to the Special Issue on Natural Language for Artificial Intelligence in the Era of LLM |
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pdf 81.2 KB |
DOI 10.17454/IJCOL102.01 | IJCOL_10_2_1 | 0,00 € |
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Cassese - Bondielli - Lenci, Evaluation of event plausibility recognition in Large (Vision)-Language Models |
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pdf 713.5 KB |
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Zamparelli, One Picture and One Thousand Words: Toward integrated multimodal generative models |
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DOI 10.17454/IJCOL102.03 | IJCOL_10_2_3 | 0,00 € |
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Ravell - Bolognesi, Yet another approximation of human semantic judgments using LLMs... but with quantized local models on novel data |
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pdf 349.8 KB |
DOI 10.17454/IJCOL102.04 | IJCOL_10_2_4 | 0,00 € |
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Everitt - Ryan - Davis et al., Large Language Models for Detecting Bias in Job Descriptions |
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pdf 628.6 KB |
DOI 10.17454/IJCOL102.05 | IJCOL_10_2_5 | 0,00 € |
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Siragusa - Pirrone, Unipa-GPT: Large Language Models for university-oriented QA in Italian |
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pdf 360.5 KB |
DOI 10.17454/IJCOL102.06 | IJCOL_10_2_6 | 0,00 € |
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Fierens - Jodogne, BERTinchamps: Cost-Effective In-House Training of Language Models in French |
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pdf 785.7 KB |
DOI 10.17454/IJCOL102.07 | IJCOL_10_2_7 | 0,00 € |
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