1 code implementation • NLPerspectives (LREC) 2022 • Marta Marchiori Manerba, Riccardo Guidotti, Lucia Passaro, Salvatore Ruggieri
Understanding and quantifying the bias introduced by human annotation of data is a crucial problem for trustworthy supervised learning.
1 code implementation • 19 May 2022 • Andrea Cossu, Tinne Tuytelaars, Antonio Carta, Lucia Passaro, Vincenzo Lomonaco, Davide Bacciu
We formalize and investigate the characteristics of the continual pre-training scenario in both language and vision environments, where a model is continually pre-trained on a stream of incoming data and only later fine-tuned to different downstream tasks.