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by evolvingstuff on 2019-04-23 (UTC).

Transformer/LSTM hybrids!!

Language Models with Transformers

"we explore effective Transformer architectures for language model, including adding additional LSTM layers to better capture the sequential context while still keeping computation efficient"https://t.co/KVWjpsACwO pic.twitter.com/4B96N4Sa57

— Thomas Lahore (@evolvingstuff) April 23, 2019
nlpresearch
by hardmaru on 2019-04-23 (UTC).

“Experimental results on the PTB, WikiText-2, and WikiText-103 show that our method achieves perplexities between 20 and 34 on all problems, i.e. on average an improvement of 12 perplexity units compared to state-of-the-art LSTMs.” 🔥 https://t.co/VB7C0KdRp8

— hardmaru (@hardmaru) April 23, 2019
researchnlp

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