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Collections including paper arxiv:2402.17764
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 579 -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 23 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 19 -
The Power of Scale for Parameter-Efficient Prompt Tuning
Paper • 2104.08691 • Published • 8
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 50 -
Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 47 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 126 -
Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 18