@inproceedings{11568_1327828,
 abstract = {This paper investigates the feasibility of employing basic prompting systems for domain-specific language models. The study focuses on bureaucratic language and uses the recently introduced BureauBERTo model for experimentation. The experiments reveal that while further pre-trained models exhibit reduced robustness concerning general knowledge, they display greater adaptability in modeling domain-specific tasks, even under a zero-shot paradigm. This demonstrates the potential of leveraging simple prompting systems in specialized contexts, providing valuable insights both for research and industry.},
 address = {Torino},
 author = {Auriemma, Serena and Madeddu, Mauro and Miliani, Martina and Bondielli, Alessando and Lenci, Alessandro and Passaro, Lucia},
 booktitle = {Proceedings of the 9th Italian Conference on Computational Linguistics},
 isbn = {979-12-5500-084-6},
 keywords = {Domain Adaptation,Italian Bureaucratic Language,Prompting,Public Administration,Transformers,Zero-shot},
 pages = {54--63},
 publisher = {Lexis Compagnia Editoriale in Torino srl},
 title = {Challenging Specialized Transformers on Zero-Shot Classification},
 year = {2024}
}