Standard American English
PulseAugur coverage of Standard American English — every cluster mentioning Standard American English across labs, papers, and developer communities, ranked by signal.
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Study finds LLMs reproduce racial stereotypes in text annotation
A withdrawn research paper found that large language models (LLMs) reproduce racial stereotypes when used for text annotation. Across 19 LLMs and over 4 million annotation judgments, the study revealed that names associ…
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LLMs rewrite African American English to Standard American English, new study finds
A new research paper details how large language models (LLMs) systematically alter African American English (AAE) into Standard American English (SAE), effectively rewriting the dialect. The study introduces a framework…
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New benchmark reveals AI detectors fail on non-Standard American English dialects
A new benchmark, DIA-HARM, has been introduced to evaluate the performance of harmful content detection models across 50 English dialects. Researchers found that these models, predominantly trained on Standard American …
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AI toxicity models show bias against African-American English
A new research paper introduces an interactive tool designed to demonstrate dialectal bias in AI toxicity models. The study found that a widely used toxicity model scored African-American English text as significantly m…
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DialectLLM framework generates diverse English dialects for AI chatbots
Researchers have developed DialectLLM, a framework designed to generate conversational data across nine distinct English dialects, moving beyond the limitations of Standard American English (SAE). This approach, created…
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LLM bias study reveals safety filters fail on explicit identity cues
A new study on arXiv investigates bias in Large Language Models (LLMs) by comparing explicit demographic profiles with implicit linguistic signals like dialect. Researchers found that LLMs often exhibit paradoxical safe…