6 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
Greater accessibility can amplify discrimination in generative AI
Carolin Holtermann, Minh Duc Bui, Kaitlyn Zhou +3
Hundreds of millions of people rely on large language models (LLMs) for education, work, and even healthcare. Yet these models are known to reproduce and amplify social biases pres…
Humans overrely on overconfident language models, across languages
Neil Rathi, Dan Jurafsky, Kaitlyn Zhou
As large language models (LLMs) are deployed globally, it is crucial that their responses are calibrated across languages to accurately convey uncertainty and limitations. Prior wo…
ELI-Why: Evaluating the Pedagogical Utility of Language Model Explanations
Brihi Joshi, Keyu He, Sahana Ramnath +5
Language models today are widely used in education, yet their ability to tailor responses for learners with varied informational needs and knowledge backgrounds remains under-explo…
Rethinking Word Similarity: Semantic Similarity through Classification Confusion
Kaitlyn Zhou, Haishan Gao, Sarah Chen +3
Word similarity has many applications to social science and cultural analytics tasks like measuring meaning change over time and making sense of contested terms. Yet traditional si…