18 citations · 29 across the 6 of their papers we have counts for
6 papers
A Standardized Machine-readable Dataset Documentation Format for Responsible AI
Nitisha Jain, Mubashara Akhtar, Joan Giner-Miguelez +15
Data is critical to advancing AI technologies, yet its quality and documentation remain significant challenges, leading to adverse downstream effects (e.g., potential biases) in AI…
Croissant: A Metadata Format for ML-Ready Datasets
Mubashara Akhtar, Omar Benjelloun, Costanza Conforti +28
Data is a critical resource for machine learning (ML), yet working with data remains a key friction point. This paper introduces Croissant, a metadata format for datasets that crea…
Building Representative Corpora from Illiterate Communities: A Review of Challenges and Mitigation Strategies for Developing Countries
Stephanie Hirmer, Alycia Leonard, Josephine Tumwesige +1
Most well-established data collection methods currently adopted in NLP depend on the assumption of speaker literacy. Consequently, the collected corpora largely fail to represent s…
Will-They-Won't-They: A Very Large Dataset for Stance Detection on Twitter
Costanza Conforti, Jakob Berndt, Mohammad Taher Pilehvar +3
We present a new challenging stance detection dataset, called Will-They-Won't-They (WT-WT), which contains 51,284 tweets in English, making it by far the largest available dataset…
Natural language processing for achieving sustainable development: the case of neural labelling to enhance community profiling
Costanza Conforti, Stephanie Hirmer, David Morgan +2
In recent years, there has been an increasing interest in the application of Artificial Intelligence - and especially Machine Learning - to the field of Sustainable Development (SD…
Neural Architectures for Open-Type Relation Argument Extraction
Benjamin Roth, Costanza Conforti, Nina Poerner +2
In this work, we introduce the task of Open-Type Relation Argument Extraction (ORAE): Given a corpus, a query entity Q and a knowledge base relation (e.g.,"Q authored notable work…