5 papers
"Not" is Not Lost in Translation: A Causal Analysis of Negation Representations in Multilingual LLMs
Giang Son Nguyen, Wray Buntine, Dung D. Le +1
Negation occurs in every language, yet its surface realization differs drastically. Despite this, multilingual large language models (LLMs) translate negation robustly, raising the…
Recurrence Is Not Enough: Causally Validating Multilingual SAE Translation Features in Gemma 2 and 3
Giang Son Nguyen, Nhi Ngoc-Yen Nguyen, Wray Buntine +1
Sparse autoencoder (SAE) features are increasingly used to explain and steer language-model behavior, but it remains unclear whether a feature found in one language context plays t…
Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
Giang Nguyen, Raghav Mehta, Emma A. M. Stanley +4
Foundation models are increasingly used as image feature extractors for mammography, but their robustness under external domain shift remains unclear. We benchmark 15 foundation-mo…
Scaling Inherently Interpretable Language Models
Guide Labs Team, Andreas Madsen, Aya Abdelsalam Ismail +7
Interpretability is often treated as a tax on capability: language models are trained as opaque systems, then explained after the fact, with methods whose reliability is difficult…
Prototype Language Models
Dan Ley, Giang Nguyen, Himabindu Lakkaraju +1
Knowing which training examples drive outputs is fundamental to auditing, correcting, and understanding language models, yet for modern LLMs this remains expensive, approximate, an…