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Found 3 papers, 2 papers with code
TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya
The absence of explicitly tailored, accessible annotated datasets for educational purposes presents a notable obstacle for NLP tasks in languages with limited resources. This study initially explores the feasibility of using machine translation (MT) to convert an existing dataset into a Tigrinya dataset in SQuAD format.
A Review of the Role of Causality in Developing Trustworthy AI Systems
This review aims to provide the reader with an overview of causal methods that have been developed to improve the trustworthiness of AI models.
Scheduling Virtual Conferences Fairly: Achieving Equitable Participant and Speaker Satisfaction
As the efficiency and fairness objectives can be in conflict with each other, we propose a joint optimization framework that allows conference organizers to design schedules that balance (i. e., allow trade-offs) among efficiency, participant fairness and speaker fairness objectives.
