34 citations · 36 across the 4 of their papers we have counts for
6 papers · 1 filter
Large Language Models Discriminate Against Speakers of German Dialects
Minh Duc Bui, Carolin Holtermann, Valentin Hofmann +2
Dialects represent a significant component of human culture and are found across all regions of the world. In Germany, more than 40% of the population speaks a regional dialect (Ad…
Fluid Language Model Benchmarking
Valentin Hofmann, David Heineman, Ian Magnusson +7
Language model (LM) benchmarking faces several challenges: comprehensive evaluations are costly, benchmarks often fail to measure the intended capabilities, and evaluation quality…
Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of Race
Lihao Sun, Chengzhi Mao, Valentin Hofmann +1
Although value-aligned language models (LMs) appear unbiased in explicit bias evaluations, they often exhibit stereotypes in implicit word association tasks, raising concerns about…
Derivational Morphology Reveals Analogical Generalization in Large Language Models
Valentin Hofmann, Leonie Weissweiler, David Mortensen +2
What mechanisms underlie linguistic generalization in large language models (LLMs)? This question has attracted considerable attention, with most studies analyzing the extent to wh…
Dialect prejudice predicts AI decisions about people's character, employability, and criminality
Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky +1
Hundreds of millions of people now interact with language models, with uses ranging from serving as a writing aid to informing hiring decisions. Yet these language models are known…
Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model
Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban +10
Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills. However, there have been relative…