Matt Murtagh White

DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects featured image
Harmful Content Detection

DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects

DIA-HARM evaluates 16 harmful content detection models across 50 English dialects using 195K+ samples, revealing 1.4–3.6% F1 drops for fine-tuned models and up to 27% for zero-shot …

avatar
Jason Lucas
•
Read more
BLUFF: Benchmarking in Low-resoUrce Languages for detecting Falsehoods and Fake news featured image
Multilingual NLP

BLUFF: Benchmarking in Low-resoUrce Languages for detecting Falsehoods and Fake news

BLUFF is the largest multilingual fake news detection benchmark, spanning 79 languages with 202K+ samples. It introduces AXL-CoI for adversarial generation and mPURIFY for quality …

avatar
Jason Lucas
•
Read more