conftrace_

Natural Language Processing

47,076 papers (54 classified directly here)

Subtopics

Applications (26,986) Resources & Methods (16,283) Generation (11,966) Understanding (7,071)

Papers per year

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Papers (including subtopics)

Sound Natural: Content Rephrasing in Dialog Systems EMNLP 2020
Facilitating the Communication of Politeness through Fine-Grained Paraphrasing EMNLP 2020
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation EMNLP 2020
Seq2Edits: Sequence Transduction Using Span-level Edit Operations EMNLP 2020
Controllable Meaning Representation to Text Generation: Linearization and Data Augmentation Strategies EMNLP 2020
Blank Language Models EMNLP 2020
COD3S: Diverse Generation with Discrete Semantic Signatures EMNLP 2020
Automatic Extraction of Rules Governing Morphological Agreement EMNLP 2020
IGT2P: From Interlinear Glossed Texts to Paradigms EMNLP 2020
Modeling Protagonist Emotions for Emotion-Aware Storytelling EMNLP 2020
Help! Need Advice on Identifying Advice EMNLP 2020
Quantifying Intimacy in Language EMNLP 2020
Writing Strategies for Science Communication: Data and Computational Analysis EMNLP 2020
Weakly Supervised Subevent Knowledge Acquisition EMNLP 2020
Biomedical Event Extraction as Sequence Labeling EMNLP 2020
Introducing a New Dataset for Event Detection in Cybersecurity Texts EMNLP 2020
CHARM: Inferring Personal Attributes from Conversations EMNLP 2020
Event Detection: Gate Diversity and Syntactic Importance Scores for Graph Convolution Neural Networks EMNLP 2020
Severing the Edge Between Before and After: Neural Architectures for Temporal Ordering of Events EMNLP 2020
How Much Knowledge Can You Pack Into the Parameters of a Language Model? EMNLP 2020
EXAMS: A Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering EMNLP 2020
End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems EMNLP 2020
Multi-Stage Pre-training for Low-Resource Domain Adaptation EMNLP 2020
ISAAQ - Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention EMNLP 2020
SubjQA: A Dataset for Subjectivity and Review Comprehension EMNLP 2020