Papers by Roberto Carlini
On the evolution of syntactic information encoded by BERT’s contextualized representations (2021.eacl-main)
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| Challenge: | Existing studies have focused on how linguistic information is encoded in pretrained language models to solve supervised tasks. |
| Approach: | They analyze how the syntax trees are embedded in the geometry of pretrained models for six different tasks, covering all levels of the linguistic structure. |
| Outcome: | The proposed model is able to learn and improve on GLUE and SQUAD, but it lacks the ability to learn the linguistic information required to solve the tasks. |
Generation of a Spanish Artificial Collocation Error Corpus (L18-1)
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| Challenge: | collocations are combinations of two elements where one (the base) is freely chosen, despite the limitations of the other (collocate) current tools for collocation error detection and correction focus on collocation validation and identification of miscollocations . |
| Approach: | They propose an algorithm for automatic generation of an artificial collocation error corpus of american English learners of Spanish that includes 17 different types of collocation errors. |
| Outcome: | The proposed algorithm can detect and classify collocation errors in learners' writings . collocation error detection and correction has not received the attention it deserves . |