Instruct GPT Insights
The discussion delves into the evolution of data for large language models, highlighting the shift from simple question-answer pairs to more complex preference rankings for model responses. Emphasis is placed on the importance of benchmark tasks to ensure labelers meet quality standards, while also acknowledging the challenges in creating these benchmarks efficiently.In this clip
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The Gradient
Kate Park: Data Engines for Vision and Language
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