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TitleStatusHype
Investigating Active Learning in Interactive Neural Machine Translation—0
Studying The Impact Of Document-level Context On Simultaneous Neural Machine Translation—0
Sentiment-based Candidate Selection for NMTCode0
Dealing with the Paradox of Quality Estimation—0
Neural Machine Translation with Inflected Lexicon—0
Text-in-Context: Token-Level Error Detection for Table-to-Text GenerationCode0
A Comparison of Sentence-Weighting Techniques for NMT—0
Controllable Sentence Simplification with a Unified Text-to-Text Transfer TransformerCode1
Formulating Neural Sentence Ordering as the Asymmetric Traveling Salesman ProblemCode0
中文关系抽取的句级语言学特征探究(A Probe into the Sentence-level Linguistic Features of Chinese Relation Extraction)—0
中文句子级性别无偏数据集构建及预训练语言模型的性别偏度评估(Construction of Chinese Sentence-Level Gender-Unbiased Data Set and Evaluation of Gender Bias in Pre-Training Language)—0
Category-Based Strategy-Driven Question Generator for Visual Dialogue—0
字里行间的道德:中文文本道德句识别研究(Morality Between the Lines: Research on Identification of Chinese Moral Sentence)—0
NS-Hunter: BERT-Cloze Based Semantic Denoising for Distantly Supervised Relation Classification—0
Sketchy Scene Captioning: Learning Multi-Level Semantic Information from Sparse Visual Scene CuesCode0
Multi-Strategy Knowledge Distillation Based Teacher-Student Framework for Machine Reading Comprehension—0
Jointly Learning Salience and Redundancy by Adaptive Sentence Reranking for Extractive Summarization—0
NHK’s Lexically-Constrained Neural Machine Translation at WAT 2021—0
The Reading Machine: A Versatile Framework for Studying Incremental Parsing Strategies—0
End-to-end mBERT based Seq2seq Enhanced Dependency Parser with Linguistic Typology knowledge—0
PIE: A Parallel Idiomatic Expression Corpus for Idiomatic Sentence Generation and Paraphrasing—0
Bering Lab’s Submissions on WAT 2021 Shared Task—0
Machine Translation with Pre-specified Target-side Words Using a Semi-autoregressive Model—0
Multi-Pair Text Style Transfer for Unbalanced Data via Task-Adaptive Meta-Learning—0
Semi-supervised Meta-learning for Cross-domain Few-shot Intent Classification—0
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