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✨Optimizing Diversity and Quality through Base-Aligned Model Collaboration
📝 Summary:
BACo is a token-level collaboration framework for LLMs. It dynamically combines a base model with its aligned counterpart to improve both output diversity and quality during inference. BACo consistently outperforms baselines, achieving significant joint improvement.
🔹 Publication Date: Published on Nov 7
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.05650
• PDF: https://arxiv.org/pdf/2511.05650
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMs #AI #MachineLearning #NLP #ModelCollaboration
📝 Summary:
BACo is a token-level collaboration framework for LLMs. It dynamically combines a base model with its aligned counterpart to improve both output diversity and quality during inference. BACo consistently outperforms baselines, achieving significant joint improvement.
🔹 Publication Date: Published on Nov 7
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.05650
• PDF: https://arxiv.org/pdf/2511.05650
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMs #AI #MachineLearning #NLP #ModelCollaboration