REALIGN is a new method designed to improve the alignment of Large Language Models (LLMs) with human values by reformatting instruction data. This approach enhances LLM performance across various metrics by aligning responses with predefined criteria and evidence.
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REALIGN is a new method designed to improve the alignment of Large Language Models (LLMs) with human values by reformatting instruction data. This approach enhances LLM performance across various metrics by aligning responses with predefined criteria and evidence.
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Key points:
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Key points:
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* REALIGN has three steps: criteria definition, retrieval augmentation, and response reformatting
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* REALIGN has three steps: criteria definition, retrieval augmentation, and response reformatting
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* It rewrites pairs (query, response) to enhance data quality for fine-tuning LLMs.
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* It rewrites pairs (query, response) to enhance data quality for fine-tuning LLMs.
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* It has shown significant improvements in general alignment, math reasoning and other tasks.
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* It has shown significant improvements in general alignment, math reasoning and other tasks.
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Congrats to the authors for their work!
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Congrats to the authors for their work!
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Paper: 
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Paper: 
Reformatted Alignment (2402.12219)
https://huggingface.co/papers/2402.12219
2402.12219
paper
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https://huggingface.co/papers/2402.12219
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Code: 
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Code: 
https://github.com/GAIR-NLP/ReAlign
https://github.com/GAIR-NLP/ReAlign
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REALIGN is a new method designed to improve the alignment of Large Language Models (LLMs) with human values by reformatting instruction data. This approach enhances LLM performance across various metrics by aligning responses with predefined criteria and evidence.

Key points:

* REALIGN has three steps: criteria definition, retrieval augmentation, and response reformatting
* It rewrites pairs (query, response) to enhance data quality for fine-tuning LLMs.
* It has shown significant improvements in general alignment, math reasoning and other tasks.

Congrats to the authors for their work!

Paper: https://huggingface.co/papers/2402.12219
Code: https://github.com/GAIR-NLP/ReAlign
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