Jianguo Zhu

RWKV: Reinventing RNNs for the Transformer Era

2023 · arXiv (Cornell University)

Transformers have revolutionized almost all natural language processing (NLP) tasks but suffer from memory and computational complexity that scales quadratically with sequence length. In contrast, recurrent neural networks (RNNs) exhibit linear scaling in memory and …

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

2022 · arXiv (Cornell University)

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions. While these capabilities have led to widespread adoption, most LLMs are developed …