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[2210.11416] Scaling Instruction-Finetuned Language Models

https://arxiv.org/abs/2210.11416
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2026-07-18 10:05:56
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Text Highlight2026-07-18 16:29:56
Original Highlight Excerpt
"arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website."
Whisper Note
I mean, cool but who actually uses arXivLabs for real work?
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arxiv.org
Text Highlight2026-07-18 13:26:56
Original Highlight Excerpt
"Code, Data and Media Associated with this Article"
Whisper Note
Just code and data? No pretrained weights? That's kinda disappointing honestly.
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arxiv.org
Text Highlight2026-07-18 13:17:56
Original Highlight Excerpt
"Code, Data and Media Associated with this Article"
Whisper Note
Wish more papers listed their datasets like this, saves hours of hunting.
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arxiv.org
Text Highlight2026-07-18 10:23:56
Original Highlight Excerpt
"Finetuning language models on a collection of datasets phrased as instructions has been shown to improve model performance and generalization to unseen tasks."
Whisper Note
I wonder if the chain-of-thought data is what really pushed it over the edge.
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arxiv.org
Text Highlight2026-07-18 10:14:56
Original Highlight Excerpt
"Finetuning language models on a collection of datasets phrased as instructions has been shown to improve model performance and generalization to unseen tasks."
Whisper Note
Honestly this matches my experience, teaching models with examples just works.
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arxiv.org
Text Highlight2026-07-18 10:05:56
Original Highlight Excerpt
"Finetuning language models on a collection of datasets phrased as instructions has been shown to improve model performance and generalization to unseen tasks."
Whisper Note
So the trick is just more tasks and bigger models? Seems too simple tbh.

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