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  • title: Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning
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            Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning
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            Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning

            Mai 3, 2021

            Sprecher:innen

            XL

            Xuebo Liu

            Řečník · 0 sledujících

            LW

            Longyue Wang

            Řečník · 1 sledující

            DW

            Derek Wong

            Řečník · 0 sledujících

            Über

            Encoder layer fusion (EncoderFusion) is a technique to fuse all the encoder layers (instead of the uppermost layer) for sequence-to-sequence (Seq2Seq) models, which has proven effective on various NLP tasks. However, it is still not entirely clear why and when EncoderFusion should work. In this paper, our main contribution is to take a step further in understanding EncoderFusion. Many of previous studies believe that the success of EncoderFusion comes from exploiting surface and syntactic inform…

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            I2

            ICLR 2021

            Účet · 897 sledujících

            Über ICLR 2021

            The International Conference on Learning Representations (ICLR) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence called representation learning, but generally referred to as deep learning. ICLR is globally renowned for presenting and publishing cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.

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