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TitleStatusHype
Dimsum @LaySumm 20Code1
Learning Pronoun Case from Distributional Cues: Flexible Frames for Case Acquisition—0
IR&TM-NJUST@CLSciSumm 20—0
Monash-Summ@LongSumm 20 SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline—0
IITP-AI-NLP-ML@ CL-SciSumm 2020, CL-LaySumm 2020, LongSumm 2020—0
HurtBERT: Incorporating Lexical Features with BERT for the Detection of Abusive Language—0
Acknowledgement Entity Recognition in CORD-19 PapersCode0
Second-Order NLP Adversarial Examples—0
Leveraging Multilingual Resources for Language Invariant Sentiment Analysis—0
Document-Level Machine Translation Evaluation Project: Methodology, Effort and Inter-Annotator Agreement—0
On the differences between human translations—0
Log-Linear Reformulation of the Noisy Channel Model for Document-Level Neural Machine Translation—0
QE Viewer: an Open-Source Tool for Visualization of Machine Translation Quality Estimation ResultsCode0
BERTering RAMS: What and How Much does BERT Already Know About Event Arguments? - A Study on the RAMS Dataset—0
Unified Humor Detection Based on Sentence-pair Augmentation and Transfer Learning—0
PosEdiOn: Post-Editing Assessment in PythOn—0
Quality In, Quality Out: Learning from Actual Mistakes—0
IESTAC: English-Italian Parallel Corpus for End-to-End Speech-to-Text Machine TranslationCode1
MTrill project: Machine Translation impact on language learning—0
Going Beyond T-SNE: Exposing whatlies in Text Embeddings—0
NHK_STRL at WNUT-2020 Task 2: GATs with Syntactic Dependencies as Edges and CTC-based Loss for Text Classification—0
Enhanced Sentence Alignment Network for Efficient Short Text Matching—0
Target Concept Guided Medical Concept Normalization in Noisy User-Generated Texts—0
Sentence Boundary Detection on Line Breaks in Japanese—0
Winners at W-NUT 2020 Shared Task-3: Leveraging Event Specific and Chunk Span information for Extracting COVID Entities from Tweets—0
CSECU-DSG at WNUT-2020 Task 2: Exploiting Ensemble of Transfer Learning and Hand-crafted Features for Identification of Informative COVID-19 English Tweets—0
Correcting the Misuse: A Method for the Chinese Idiom Cloze Test—0
Evaluation of Transfer Learning for Adverse Drug Event (ADE) and Medication Entity Extraction—0
Learning from Unlabelled Data for Clinical Semantic Textual Similarity—0
Various Approaches for Predicting Stroke Prognosis using Magnetic Resonance Imaging Text Records—0
Where’s the Question? A Multi-channel Deep Convolutional Neural Network for Question Identification in Textual Data—0
Chunk-based Chinese Spelling Check with Global Optimization—0
Representation Learning for Type-Driven CompositionCode0
Approximation of Response Knowledge Retrieval in Knowledge-grounded Dialogue GenerationCode0
Enhancing Generalization in Natural Language Inference by SyntaxCode0
Enhancing Automated Essay Scoring Performance via Fine-tuning Pre-trained Language Models with Combination of Regression and Ranking—0
Effective Crowd-Annotation of Participants, Interventions, and Outcomes in the Text of Clinical Trial ReportsCode0
A Corpus of Very Short Scientific Summaries—0
An Instance Level Approach for Shallow Semantic Parsing in Scientific Procedural Text—0
Looking inside Noun Compounds: Unsupervised Prepositional and Free Paraphrasing—0
MRP 2020: The Second Shared Task on Cross-Framework and Cross-Lingual Meaning Representation Parsing—0
The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction—0
Cross-Lingual Dependency Parsing by POS-Guided Word Reordering—0
\'UFAL at MRP 2020: Permutation-invariant Semantic Parsing in PERINCode1
A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events—0
Multi-Agent Mutual Learning at Sentence-Level and Token-Level for Neural Machine Translation—0
Optimizing Word Segmentation for Downstream TaskCode1
A Shared-Private Representation Model with Coarse-to-Fine Extraction for Target Sentiment Analysis—0
Question Answering with Long Multiple-Span AnswersCode1
A Semi-supervised Approach to Generate the Code-Mixed Text using Pre-trained Encoder and Transfer Learning—0
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