Power Law Graph Transformer for Machine Translation and Representation Learning

27 June 2021

Papers citing "Power Law Graph Transformer for Machine Translation and Representation Learning"

5 / 5 papers shown

Title
PLDR-LLMs Learn A Generalizable Tensor Operator That Can Replace Its Own Deep Neural Net At Inference Burc Gokden 57 0 0 19 Feb 2025
PLDR-LLM: Large Language Model from Power Law Decoder Representations Burc Gokden 31 1 0 22 Oct 2024
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhehuai Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 718 6,750 0 26 Sep 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 223 7,930 0 17 Aug 2015
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 322 31,297 0 16 Jan 2013