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Landmark Attention_ Random-Access Infinite Context Length for Transformers_ arxiv2305.16300.pdf

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Landmark Attention_ Random-Access Infinite Context Length for Transformers_ arxiv2305.16300.pdf
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Llama 2_ Open Foundation and Fine-Tuned Chat Models_ arxiv2307.09288.pdf
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LLaMA_ Open and Efficient Foundation Language Models_ arxiv2302.13971.pdf
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Photonic Matrix Computing_ From Fundamentals to Applications_ Junwei Cheng_ Hailong Zhou_ Jianji Dong_ Nanomaterials 2021.pdf.pdf
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GQA_ Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints_ arxiv2305.13245.pdf
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RoFormer_ Enhanced Transformer with Rotary Position Embedding_ arxiv2104.09864v4.pdf
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GLU Variants Improve Transformer_arxiv2002.05202.pdf
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SentencePiece_ A simple and language independent subword tokenizer and detokenizer for Neural Text Processing_ arxiv1808.06226.pdf
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Extending Context Window of Large Language Models via Positional Interpolation_ arxiv2306.15595.pdf
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Stay on topic with Classifier-Free Guidance_ arxiv2306.17806.pdf
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Efficient streaming language models with attention sinks_ arxiv2309.17453.pdf
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Climbing towards Natural Language Understanding_ On Meaning Form and Understanding in the Age of Data_ Emily M Bender- Alexander Koller_ 2020.pdf
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The Curse of Recursion_ Training on Generated Data Makes Models Forget_ arxiv2305.17493.pdf
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The Poison of Alignment_ arxiv2308.13449.pdf
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Are Emergent Abilities of Large Language Models a Mirage_ arxiv2304.15004.pdf
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An Ultra-Low Energy Internally Analog, Externally Digital Vector-Matrix Multiplier Based on NOR Flash Memory Technology_ M Reza Mahmoodi_ Dmitri Strukov_ 2018.pdf
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The Transformer Model in Equations_ John Thickstun_ 2023.pdf
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The case for 4-bit precision_ k-bit Inference Scaling Laws_ arxiv2212.09720.pdf
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Train Short, Test Long_ Attention with Linear Biases Enables Input Length Extrapolation_arxiv2108.12409.pdf
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Unigram Algorithm_ Subword Regularization_ Improving Neural Network Translation Models with Multiple Subword Candidates_ arxiv1804.10959.pdf
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