الباحثون

David Jurgens

المنشورات 2

نسخة أولية وصول مفتوح

HARISSA: Inference-Time Self-Checks for Efficient and Safe Local Language Model Deployment

Kenan Alkiek, Moontae Lee, David Jurgens وآخرون · 2026

Running a language model locally offers advantages in privacy, latency, and cost, but local hardware fits only small models, which are less capable than frontier models. The usual remedy for a hard query, escalating it to a cloud model, gives up the privacy and cost advantages of running locally. A deployment that stay …

نسخة أولية وصول مفتوح

Lost in Translation: Measuring the Effect of Non-Native English on End User Performance of Large Language Models

Yusheng Zhou, Eleanor Lin, David Jurgens · 2026

Large language models (LLMs) are increasingly used by people whose first language is not English, yet these users have been shown to receive systematically lower-quality responses than fluent speakers. Which specific features of non-native English drive this gap remains unclear, because fluency is itself a composite of …

المؤلفون المشاركون