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Found 8 papers, 2 papers with code
Data Caricatures: On the Representation of African American Language in Pretraining Corpora
With a combination of quantitative experiments, human judgments, and qualitative analyses, we evaluate the quantity and quality of African American Language (AAL) representation in 12 predominantly English, open-source pretraining corpora.
Evaluation of African American Language Bias in Natural Language Generation
We evaluate how well LLMs understand African American Language (AAL) in comparison to their performance on White Mainstream English (WME), the encouraged "standard" form of English taught in American classrooms.
SafeText: A Benchmark for Exploring Physical Safety in Language Models
Understanding what constitutes safe text is an important issue in natural language processing and can often prevent the deployment of models deemed harmful and unsafe.
Mitigating Covertly Unsafe Text within Natural Language Systems
An increasingly prevalent problem for intelligent technologies is text safety, as uncontrolled systems may generate recommendations to their users that lead to injury or life-threatening consequences.
Detecting and Reducing Bias in a High Stakes Domain
Gang-involved youth in cities such as Chicago sometimes post on social media to express their aggression towards rival gangs and previous research has demonstrated that a deep learning approach can predict aggression and loss in posts.
Detecting Gang-Involved Escalation on Social Media Using Context
Gang-involved youth in cities such as Chicago have increasingly turned to social media to post about their experiences and intents online.
Multimodal Social Media Analysis for Gang Violence Prevention
In this paper we partnered computer scientists with social work researchers, who have domain expertise in gang violence, to analyze how public tweets with images posted by youth who mention gang associations on Twitter can be leveraged to automatically detect psychosocial factors and conditions that could potentially assist social workers and violence outreach workers in prevention and early intervention programs.
Automatically Processing Tweets from Gang-Involved Youth: Towards Detecting Loss and Aggression
Violence is a serious problems for cities like Chicago and has been exacerbated by the use of social media by gang-involved youths for taunting rival gangs.
