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Found 11 papers, 1 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.
PseudoSeer: a Search Engine for Pseudocode
A novel pseudocode search engine is designed to facilitate efficient retrieval and search of academic papers containing pseudocode.
Hey GPT, Can You be More Racist? Analysis from Crowdsourced Attempts to Elicit Biased Content from Generative AI
The widespread adoption of large language models (LLMs) and generative AI (GenAI) tools across diverse applications has amplified the importance of addressing societal biases inherent within these technologies.
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing
This study focuses on the topic of LLMs assist NLP Researchers, particularly examining the effectiveness of LLM in assisting paper (meta-)reviewing and its recognizability.
Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLP
With the rapid proliferation of artificial intelligence, there is growing concern over its potential to exacerbate existing biases and societal disparities and introduce novel ones.
An Audit on the Perspectives and Challenges of Hallucinations in NLP
Through the examination of the literature, we identify a lack of agreement with the term `hallucination' in the field of NLP.
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.
