Qualitative study of 19 practitioners reveals ten LLM product evaluation practices and introduces the results-actionability gap as a key barrier to turning findings into improvements.
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Interviews in a semiconductor company reveal 16 collaboration and communication challenges in ML engineering teams, with unclear roles and responsibilities as the top issue, and list effective mitigation practices under hardware-driven constraints.
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Results-Actionability Gap: Understanding How Practitioners Evaluate LLM Products in the Wild
Qualitative study of 19 practitioners reveals ten LLM product evaluation practices and introduces the results-actionability gap as a key barrier to turning findings into improvements.
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Exploring CoCo Challenges in ML Engineering Teams: Insights From the Semiconductor Industry
Interviews in a semiconductor company reveal 16 collaboration and communication challenges in ML engineering teams, with unclear roles and responsibilities as the top issue, and list effective mitigation practices under hardware-driven constraints.