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Found 6 papers, 0 papers with code
Enhanced Labelling in Active Learning for Coreference Resolution
In this paper we describe our attempt to increase the amount of information that can be retrieved through active learning sessions compared to previous approaches.
Uncertainty and Inclusivity in Gender Bias Annotation: An Annotation Taxonomy and Annotated Datasets of British English Text
Mitigating harms from gender biased language in Natural Language Processing (NLP) systems remains a challenge, and the situated nature of language means bias is inescapable in NLP data.
Beyond Explanation: A Case for Exploratory Text Visualizations of Non-Aggregated, Annotated Datasets
This paper presents an overview of text visualization techniques relevant for data perspectivism, aiming to facilitate analysis of annotated datasets for the datasets’ creators and stakeholders.
ChatGPT in Data Visualization Education: A Student Perspective
Unlike traditional educational chatbots that rely on pre-programmed responses, large-language model-driven chatbots, such as ChatGPT, demonstrate remarkable versatility and have the potential to serve as a dynamic resource for addressing student needs from understanding advanced concepts to solving complex problems.
Feature-Action Design Patterns for Storytelling Visualizations with Time Series Data
Motivated initially by the need to communicate time series data during the COVID-19 pandemic, we developed a novel computer-assisted method for meta-authoring of stories, which enables the design of storyboards that include feature-action patterns in anticipation of potential features that may appear in dynamically arrived or selected data.
Situated Data, Situated Systems: A Methodology to Engage with Power Relations in Natural Language Processing Research
We propose a bias-aware methodology to engage with power relations in natural language processing (NLP) research.
