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🔥🚀🌟 New Research Alert - YOCO! 🌟🚀🔥
🔥🚀🌟 New Research Alert - YOCO! 🌟🚀🔥
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📄 Title: You Only Cache Once: Decoder-Decoder Architectures for Language Models 🔝
📄 Title: You Only Cache Once: Decoder-Decoder Architectures for Language Models 🔝
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📝 Description: YOCO is a novel decoder-decoder architecture for LLMs that reduces memory requirements, speeds up prefilling, and maintains global attention. It consists of a self-decoder for encoding KV caches and a cross-decoder for reusing these caches via cross-attention.
📝 Description: YOCO is a novel decoder-decoder architecture for LLMs that reduces memory requirements, speeds up prefilling, and maintains global attention. It consists of a self-decoder for encoding KV caches and a cross-decoder for reusing these caches via cross-attention.
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👥 Authors: Yutao Sun et al.
👥 Authors: Yutao Sun et al.
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📄 Paper: 
📄 Paper: 
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https://huggingface.co/papers/2405.05254
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2405.05254
https://huggingface.co/papers/2405.05254
You Only Cache Once: Decoder-Decoder Architectures for Language Models (2405.05254)
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📁 Repository: 
📁 Repository: 
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https://github.com/microsoft/unilm/tree/master/YOCO
https://github.com/microsoft/unilm/tree/master/YOCO
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📚 More Papers: more cutting-edge research presented at other conferences in the 
📚 More Papers: more cutting-edge research presented at other conferences in the 
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https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers
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DmitryRyumin/NewEraAI-Papers
https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers
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 curated by 
 curated by 
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@DmitryRyumin
DmitryRyumin
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🔍 Keywords: #YOCO #DecoderDecoder #LargeLanguageModels #EfficientArchitecture #GPUMemoryReduction #PrefillingSpeedup #GlobalAttention #DeepLearning #Innovation #AI
🔍 Keywords: #YOCO #DecoderDecoder #LargeLanguageModels #EfficientArchitecture #GPUMemoryReduction #PrefillingSpeedup #GlobalAttention #DeepLearning #Innovation #AI
🔥🚀🌟 New Research Alert - YOCO! 🌟🚀🔥
📄 Title: You Only Cache Once: Decoder-Decoder Architectures for Language Models 🔝

📝 Description: YOCO is a novel decoder-decoder architecture for LLMs that reduces memory requirements, speeds up prefilling, and maintains global attention. It consists of a self-decoder for encoding KV caches and a cross-decoder for reusing these caches via cross-attention.

👥 Authors: Yutao Sun et al.

📄 Paper: https://huggingface.co/papers/2405.05254

📁 Repository: https://github.com/microsoft/unilm/tree/master/YOCO

📚 More Papers: more cutting-edge research presented at other conferences in the https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin

🔍 Keywords: #YOCO #DecoderDecoder #LargeLanguageModels #EfficientArchitecture #GPUMemoryReduction #PrefillingSpeedup #GlobalAttention #DeepLearning #Innovation #AI
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