Results 61 to 62 of about 65 (62)
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2017
Рданной ÑабоÑе ÑаÑÑмаÑÑиваеÑÑÑ Ð¾Ð´Ð½Ð° из нелинейнÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ кÑиÑÑалла, опиÑаннÑÑ ÐнÑико ФеÑми. ÐлÑÑевÑм оÑлиÑием ÑвлÑеÑÑÑ Ð²Ð²ÐµÐ´ÐµÐ½Ð¸Ðµ Ñепловой ÑнеÑгии ÑеÑез задание диÑпеÑÑии наÑалÑнÑÑ ÑкоÑоÑÑей.
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Рданной ÑабоÑе ÑаÑÑмаÑÑиваеÑÑÑ Ð¾Ð´Ð½Ð° из нелинейнÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹ кÑиÑÑалла, опиÑаннÑÑ ÐнÑико ФеÑми. ÐлÑÑевÑм оÑлиÑием ÑвлÑеÑÑÑ Ð²Ð²ÐµÐ´ÐµÐ½Ð¸Ðµ Ñепловой ÑнеÑгии ÑеÑез задание диÑпеÑÑии наÑалÑнÑÑ ÑкоÑоÑÑей.
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The purpose of this work is to develop a method for preventing confidential data leaks using a lightweight large language model. Research objectives: 1. Study lightweight LLMs to identify confidential information and justify the choice of the most suitable model for further improvement. 2. Improve the accuracy of the selected LLM. 3.
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