6 papers · 1 filter
From Model to Classroom: Evaluating Generated MCQs for Portuguese with Narrative and Difficulty Concerns
Bernardo Leite, Henrique Lopes Cardoso, Pedro Pinto +4
While MCQs are valuable for learning and evaluation, manually creating them with varying difficulty levels and targeted reading skills remains a time-consuming and costly task. Rec…
Advancing Question Generation with Joint Narrative and Difficulty Control
Bernardo Leite, Henrique Lopes Cardoso
Question Generation (QG), the task of automatically generating questions from a source input, has seen significant progress in recent years. Difficulty-controllable QG (DCQG) enabl…
FairytaleQA Translated: Enabling Educational Question and Answer Generation in Less-Resourced Languages
Bernardo Leite, Tomás Freitas Osório, Henrique Lopes Cardoso
Question Answering (QA) datasets are crucial in assessing reading comprehension skills for both machines and humans. While numerous datasets have been developed in English for this…
PORTULAN ExtraGLUE Datasets and Models: Kick-starting a Benchmark for the Neural Processing of Portuguese
Tomás Osório, Bernardo Leite, Henrique Lopes Cardoso +4
Leveraging research on the neural modelling of Portuguese, we contribute a collection of datasets for an array of language processing tasks and a corresponding collection of fine-t…
On Few-Shot Prompting for Controllable Question-Answer Generation in Narrative Comprehension
Bernardo Leite, Henrique Lopes Cardoso
Question Generation aims to automatically generate questions based on a given input provided as context. A controllable question generation scheme focuses on generating questions w…
Fostering the Ecosystem of Open Neural Encoders for Portuguese with Albertina PT* Family
Rodrigo Santos, João Rodrigues, Luís Gomes +5
To foster the neural encoding of Portuguese, this paper contributes foundation encoder models that represent an expansion of the still very scarce ecosystem of large language model…