Low-Resource Languages

Multilingual NLP

Position: Breaking the Dual Curse of Multilingual AI Requires Socio-Technical Guardrails, Not Post-Hoc Alignment

A position paper arguing that the dual curse of multilingual AI — 35% harmful generation and near-random reward-model accuracy in low-resource languages — cannot be fixed by …

avatar
Jason S. Lucas, Ph.D., MPH, M.Sc.
•
Read more
Multilingual NLP featured image
Multilingual NLP

Multilingual NLP

Detecting fake news, false claims, and machine-generated text across languages and low-resource settings.

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 S. Lucas, Ph.D., MPH, M.Sc.
•
Read more
Equity, Inclusion & the Digital Language Divide featured image
AI Ethics

Equity, Inclusion & the Digital Language Divide

Examining how AI systems disproportionately impact long-tail users and speakers of underserved languages.

Read more