In this talk, we will examine how LLM outputs are evaluated by potential end users versus professional linguist-annotators, as two ways of ensuring alignment with real-world user needs and expectations. We will compare the two approaches, highlight the advantages and recurring pitfalls of user-driven annotation, and share the mitigation techniques we have developed from our own experience.
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Speaker
Yulia Khalus
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talks
Computational Linguist
Grammarly
Yulia Khalus—сomputational linguist at Grammarly. Works on such features as correctness, enhancement, and quick replies. Background: MA in translation (French-Ukrainian).
Bio from: The Depth and Breadth of Language Research and Engineering at Grammarly
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