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Found 8 papers, 1 papers with code
Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic Variations
Commercial content moderation APIs are marketed as scalable solutions to combat online hate speech.
Writer-Defined AI Personas for On-Demand Feedback Generation
This is challenging, as writers may struggle to empathize with readers, get feedback in time, or gain access to the target group.
Methods for the Design and Evaluation of HCI+NLP Systems
HCI and NLP traditionally focus on different evaluation methods.
More Than Accuracy: Towards Trustworthy Machine Learning Interfaces for Object Recognition
This paper investigates the user experience of visualizations of a machine learning (ML) system that recognizes objects in images.
How Fake News Affect Trust in the Output of a Machine Learning System for News Curation
In a study with 82 vocational school students with a background in IT, we found that users are able to provide trust ratings that distinguish trustworthy recommendations of quality news stories from untrustworthy recommendations.
Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation
Attention mechanisms have seen some success for natural language processing downstream tasks in recent years and generated new State-of-the-Art results.
Generating captions without looking beyond objects
This paper explores new evaluation perspectives for image captioning and introduces a noun translation task that achieves comparative image caption generation performance by translating from a set of nouns to captions.
Text comparison using word vector representations and dimensionality reduction
This paper describes a technique to compare large text sources using word vector representations (word2vec) and dimensionality reduction (t-SNE) and how it can be implemented using Python.
