Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

Crowdsensing has received widespread attention in recent years. It is extensively employed
in smart cities and intelligent transportation systems. This paper comprehensively surveys …

Human evaluations are typically considered the gold standard in natural language
generation, but as models' fluency improves, how well can evaluators detect and judge …

AI models are increasingly applied in high-stakes domains like health and conservation.
Data quality carries an elevated significance in high-stakes AI due to its heightened …

Abstract Many tasks in Natural Language Processing (NLP) and Computer Vision (CV) offer
evidence that humans disagree, from objective tasks such as part-of-speech tagging to more …

Computer vision models have known performance disparities across attributes such as
gender and skin tone. This means during tasks such as classification and detection, model …

Data collection is a major bottleneck in machine learning and an active research topic in
multiple communities. There are largely two reasons data collection has recently become a …

The recent advancement in digital twin technology, which creates virtual replicas of real-
world processes, offers an interactive testbed for understanding and predicting …

Diversity in datasets is a key component to building responsible AI/ML. Despite this
recognition, we know little about the diversity among the annotators involved in data …

Recent research has demonstrated that cognitive biases such as the confirmation bias or the
anchoring effect can negatively affect the quality of crowdsourced data. In practice, however …