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LILT AI research

LILT is driving the future of language technology

Large Language Models
Large Language Models

LILT's large language models are fine-tuned in real-time, as translators work, updating parameters automatically with each sentence translated. This tight loop allows adaptation to specific document-level and project-level vocabulary, structural patterns, and idiosyncrasies. Our research team focuses on the fast and effective contextualization of state-of-the-art neural machine translation models using methods that are efficient enough to support large-scale, personalized neural machine translation.

Contextual AI
Contextual AI

Contextual AI for enterprise translation doesn’t just enable the translation of full sentences in isolation; it must make suggestions with deep business and content context — predicting what translators will type next, how they will transfer formatting from the source document to the target, and what edits will be performed by reviewers. Truly interactive systems must take termbases, translation memories, and contextual constraints into account for all of these suggestions. Our research team focuses on the full range of automatically generated suggestions that can improve the speed and quality of human localization work across translation, reviewing, and quality assurance.

Human-Computer Interaction and Data Science for Localization
Human-Computer Interaction and Data Science for Localization

LILT's unique approach to localization places both professional translators and artificial intelligence technology together at the core of our operations. A broad range of human-computer interaction problems arise in this setting, from text-editing interfaces to assigning translators to project workflows. Our research team focuses on interaction design across the LILT platform and data science across LILT's business and translator community.

Meet the LILT Research Team

John DeNero
John DeNero
Co-Founder and Chief Scientist
Spence Green
Spence Green
Co-founder and CEO
Joern Wuebker
Joern Wuebker
Director of Research
Patrick Simianer
Patrick Simianer
Principal Research Scientist
Gabriel Bretschner
Gabriel Bretschner
Research Scientist
Aditya Shastry
Aditya Shastry
Research Scientist
Kaden Uhlig
Kaden Uhlig
Research Scientist
Raphael Reinauer
Raphael Reinauer
Research Scientist
Farid Yagubbayli
Farid Yagubbayli
Research Engineer
Jonas Levy Alfie
Jonas Levy Alfie
Research Engineer
Alexandru Popa
Alexandru Popa
Research Engineer
Inceptive technology that understands all people and culture

"So many interesting translation problems touch on cultural issues and contextual clues. If we really want to reach what we would consider the highest possible level of quality achievable, we have to build technology that better understands all people and cultures."

Inceptive technology that understands all people and culture
Jakob Uszkoreit
Co-founder at Inceptive

Our Advisors

Franz Och
Franz Och
Chief Architect of Google Translate
Chris Manning
Chris Manning
Professor of Computer Science, Stanford
Jeffrey Heer
Jeffrey Heer
Professor of Computer Science, UW

Start your AI journey with LILT today