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Found 7 papers, 0 papers with code
A Study of Implicit Bias in Pretrained Language Models against People with Disabilities
Pretrained language models (PLMs) have been shown to exhibit sociodemographic biases, such as against gender and race, raising concerns of downstream biases in language technologies.
"Confidently Nonsensical?'': A Critical Survey on the Perspectives and Challenges of 'Hallucinations' in NLP
We investigate how hallucination in large language models (LLM) is characterized in peer-reviewed literature using a critical examination of 103 publications across NLP research.
Automated Detection and Analysis of Data Practices Using A Real-World Corpus
Privacy policies are crucial for informing users about data practices, yet their length and complexity often deter users from reading them.
The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis
We conduct an inquiry into the sociotechnical aspects of sentiment analysis (SA) by critically examining 189 peer-reviewed papers on their applications, models, and datasets.
Leveraging Twitter Data for Sentiment Analysis of Transit User Feedback: An NLP Framework
First, it utilizes few-shot learning for tweet classification within predefined categories, allowing effective identification of the issues described in tweets.
Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models
We analyze sentiment analysis and toxicity detection models to detect the presence of explicit bias against people with disability (PWD).
Privacy at Scale: Introducing the PrivaSeer Corpus of Web Privacy Policies
Organisations disclose their privacy practices by posting privacy policies on their website.
