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[2306.02707] Orca: Progressive Learning from Complex Explanation Traces of GPT-4

https://arxiv.org/abs/2306.02707
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2026-07-16 09:43:33
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arxiv.org
划选高亮2026-07-16 16:07:33
原文高亮摘录
“arXivLabs is a framework that allows collaborators to develop and share new arXiv features”
Whisper 随想笔记
Sounds like a cool way for devs to plug in their ideas.
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arxiv.org
划选高亮2026-07-16 13:04:33
原文高亮摘录
“Recent research has focused on enhancing the capability of smaller models through imitation learning”
Whisper 随想笔记
I tried Orca-style fine-tuning once, the explanation traces really do make a difference, underrated trick.
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arxiv.org
划选高亮2026-07-16 12:55:33
原文高亮摘录
“Recent research has focused on enhancing the capability of smaller models through imitation learning”
Whisper 随想笔记
Imitation learning is cool but honestly the eval part is the real kicker—so many papers overhype their small models.
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arxiv.org
划选高亮2026-07-16 10:01:33
原文高亮摘录
“Orca: Progressive Learning from Complex Explanation Traces of GPT-4”
Whisper 随想笔记
Would love to see how this handles tasks beyond explanation traces.
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arxiv.org
划选高亮2026-07-16 09:52:33
原文高亮摘录
“Orca: Progressive Learning from Complex Explanation Traces of GPT-4”
Whisper 随想笔记
Progressive learning is key, but I wonder how scalable this really is.
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arxiv.org
划选高亮2026-07-16 09:43:33
原文高亮摘录
“Orca: Progressive Learning from Complex Explanation Traces of GPT-4”
Whisper 随想笔记
Sounds like they're just copying GPT-4's homework, not really learning.

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