15 citations · 38 across the 11 of their papers we have counts for
11 papers
On Synthetic Data for Back Translation
Jiahao Xu, Yubin Ruan, Wei Bi +4
Back translation (BT) is one of the most significant technologies in NMT research fields. Existing attempts on BT share a common characteristic: they employ either beam search or r…
Rethinking Translation Memory Augmented Neural Machine Translation
Hongkun Hao, Guoping Huang, Lemao Liu +3
This paper rethinks translation memory augmented neural machine translation (TM-augmented NMT) from two perspectives, i.e., a probabilistic view of retrieval and the variance-bias…
Effidit: Your AI Writing Assistant
Shuming Shi, Enbo Zhao, Duyu Tang +10
In this technical report, we introduce Effidit (Efficient and Intelligent Editing), a digital writing assistant that facilitates users to write higher-quality text more efficiently…
Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics
Jiannan Xiang, Huayang Li, Yahui Liu +4
Current practices in metric evaluation focus on one single dataset, e.g., Newstest dataset in each year's WMT Metrics Shared Task. However, in this paper, we qualitatively and quan…
Visualizing the Relationship Between Encoded Linguistic Information and Task Performance
Jiannan Xiang, Huayang Li, Defu Lian +3
Probing is popular to analyze whether linguistic information can be captured by a well-trained deep neural model, but it is hard to answer how the change of the encoded linguistic…
Exploring and Adapting Chinese GPT to Pinyin Input Method
Minghuan Tan, Yong Dai, Duyu Tang +5
While GPT has become the de-facto method for text generation tasks, its application to pinyin input method remains unexplored. In this work, we make the first exploration to levera…
On the Branching Bias of Syntax Extracted from Pre-trained Language Models
Huayang Li, Lemao Liu, Guoping Huang +1
Many efforts have been devoted to extracting constituency trees from pre-trained language models, often proceeding in two stages: feature definition and parsing. However, this kind…
Evaluating Explanation Methods for Neural Machine Translation
Jierui Li, Lemao Liu, Huayang Li +3
Recently many efforts have been devoted to interpreting the black-box NMT models, but little progress has been made on metrics to evaluate explanation methods. Word Alignment Error…
Regularized Context Gates on Transformer for Machine Translation
Xintong Li, Lemao Liu, Rui Wang +2
Context gates are effective to control the contributions from the source and target contexts in the recurrent neural network (RNN) based neural machine translation (NMT). However,…
Neural Machine Translation with Noisy Lexical Constraints
Huayang Li, Guoping Huang, Deng Cai +1
Lexically constrained decoding for machine translation has shown to be beneficial in previous studies. Unfortunately, constraints provided by users may contain mistakes in real-wor…
Language-Independent Representor for Neural Machine Translation
Long Zhou, Yuchen Liu, Jiajun Zhang +2
Current Neural Machine Translation (NMT) employs a language-specific encoder to represent the source sentence and adopts a language-specific decoder to generate target translation.…