Categories: FAANG

Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution

Large language models (LLMs) have achieved impressive performance, leading to their widespread adoption as decision-support tools in resource-constrained contexts like hiring and admissions. There is, however, scientific consensus that AI systems can reflect and exacerbate societal biases, raising concerns about identity-based harm when used in critical social contexts. Prior work has laid a solid foundation for assessing bias in LLMs by evaluating demographic disparities in different language reasoning tasks. In this work, we extend single-axis fairness evaluations to examine intersectional…
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What tools would you use to make morphing videos like this?

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DeepMind introduces AI agent that learns to complete various tasks in a scalable world model

Over the past decade, deep learning has transformed how artificial intelligence (AI) agents perceive and…

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