Denise Diaz — accepted AI-conference papers

2026

MENLO: From Preferences to Proficiency – Evaluating and Modeling Native-like Quality Across 47 Languages

Chenxi Whitehouse, Sebastian Ruder, Tony Zhiyang Lin, Oksana Kurylo, Haruka Takagi, Janice Lam +2

ICLR 2026poster

Ensuring native-like quality of large language model (LLM) responses across many languages is challenging. To address this, we introduce MENLO, a framework that operationalizes the evaluation of native-like response quality based on audience design-inspired mechanisms. Using MENLO, we create a datas…

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2021

Gender bias amplification during Speed-Quality optimization in Neural Machine Translation

Adithya Renduchintala, Denise Diaz, Kenneth Heafield, Xian Li, Mona Diab

ACL 2021short

Is bias amplified when neural machine translation (NMT) models are optimized for speed and evaluated on generic test sets using BLEU? We investigate architectures and techniques commonly used to speed up decoding in Transformer-based models, such as greedy search, quantization, average attention net…

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