[2412.16429] LearnLM: Improving Gemini for Learning

View the PDF file from the paper titled Learnlm: Gemini Recruitment, by Tearnlm Team Google: Abhinit Modi and 44 other books

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a summary:Trucchared artificial intelligence systems are adjusted today to provide information by default, instead of involving users in the learning service as a human teacher. To address a wide range of cases of potential education for these systems, we reformulate the challenge of injecting educational behavior as one of the following educational instructions \ TEXTIT {the following educational instructions}, where examples of training and evaluation include instructions at the system level that describe the features of the existing or required teaching assets required in subsequent typical turns. This framework avoids committing our models with any specific definition of teaching assets, and instead allows teachers or developers to determine the behavior of the required model. It also wipes a way to improve Gemini for learning-by enabling the addition of our educational data to post-training mixtures-besides the extensive capacity group quickly. Both are important changes from our primary technology report. We explain how training with the following educational instructions produces a learning model (available on Google AI Studio) greatly by experts through a variety of learning scenarios, with average preferential strengths for +31 \ % more than GPT-4O, +11 \ % on Claude 3.5 Sonnet, +13 \ % on Gemini 1.5 Pro which was it Its matter.