Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence
Learning

Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning

29 December 2020

Liang Ding

Papers citing "Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning"

9 / 9 papers shown

Title
DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers Anna Langedijk Hosein Mohebbi Gabriele Sarti Willem H. Zuidema Jaap Jumelet 32 10 0 05 Oct 2023
EIT: Enhanced Interactive Transformer Tong Zheng Bei Li Huiwen Bao Tong Xiao Jingbo Zhu 32 2 0 20 Dec 2022
Breaking the Representation Bottleneck of Chinese Characters: Neural Machine Translation with Stroke Sequence Modeling Zhijun Wang Xuebo Liu Min Zhang 27 11 0 23 Nov 2022
Revisiting Grammatical Error Correction Evaluation and Beyond Peiyuan Gong Xuebo Liu Heyan Huang Min Zhang 31 16 0 03 Nov 2022
Depth-Wise Attention (DWAtt): A Layer Fusion Method for Data-Efficient Classification Muhammad N. ElNokrashy Badr AlKhamissi Mona T. Diab MoMe 25 4 0 30 Sep 2022
E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generation Qihuang Zhong Liang Ding Juhua Liu Bo Du Dacheng Tao 49 27 0 30 May 2022
Grounding Commands for Autonomous Vehicles via Layer Fusion with Region-specific Dynamic Layer Attention Hou Pong Chan M. Guo Chengguang Xu 30 4 0 14 Mar 2022
Improving Neural Machine Translation by Denoising Training Liang Ding Keqin Peng Dacheng Tao VLM AI4CE 41 6 0 19 Jan 2022
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Z. Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 716 6,746 0 26 Sep 2016