2.1k citations · 2.4k across the 5 of their papers we have counts for
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cs.LG2022★ 57 cited
Efficiently Scaling Transformer Inference
Reiner Pope, Sholto Douglas, Aakanksha Chowdhery +7
We study the problem of efficient generative inference for Transformer models, in one of its most challenging settings: large deep models, with tight latency targets and long seque…
cs.CL2022★ 2.1k cited
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin +64
Large language models have been shown to achieve remarkable performance across a variety of natural language tasks using few-shot learning, which drastically reduces the number of…