Join Kostia Omelianchuk and Lukas Beisteiner as they unpack the full scope of Grammatical Error Correction (GEC) from task framing, evaluation, and training to inference optimization and serving high-performance production systems at Grammarly. They will discuss: The modern GEC recipe (shift from heavily human-annotated corpora to semi-synthetic data generation), LLM-as-a-judge techniques for scalable evaluation, and techniques to make deployment fast and affordable, including Speculative Decoding.
talk-data.com
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Speaker
Lukas Beisteiner
1
talks
ML Engineer
Grammarly
ML engineer focused on production-ready ML systems, scalability, and deployment for Grammarly.
Bio from: LLMs Aren’t Just for Chat: Grammatical Error Correction at Scale
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