A Comprehensive Dictionary and Term Variation Analysis for COVID-19 and SARS-CoV-2
Comments Accepted EMNLP NLP-COVID Workshop
期刊&会议
EMNLP
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
On the diminishing return of labeling clinical reports
Comments Accepted at the EMNLP 2020 Clinical NLP workshop, 9 pages + 2 for references, 7 figures, 4 tables
DGST: a Dual-Generator Network for Text Style Transfer
Comments Accepted by EMNLP 2020, camera ready version
Coarse-to-Fine Pre-training for Named Entity Recognition
Journal ref EMNLP 2020
Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis
Comments EMNLP 2020, long paper
Why and when should you pool? Analyzing Pooling in Recurrent Architectures
Comments Accepted to Findings of EMNLP 2020, to be presented at BlackBoxNLP. Updated Version
Active Sentence Learning by Adversarial Uncertainty Sampling in Discrete Space
Comments Accepted to EMNLP 2020 Findings
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles
Comments EMNLP 2020
Event Detection: Gate Diversity and Syntactic Importance Scoresfor Graph Convolution Neural Networks
Comments EMNLP 2020
MMFT-BERT: Multimodal Fusion Transformer with BERT Encodings for Visual Question Answering
Comments Accepted at Findings of EMNLP 2020
To BERT or Not to BERT: Comparing Task-specific and Task-agnostic Semi-Supervised Approaches for Sequence Tagging
Comments Accepted in the Proceedings of 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)(https://2020.emnlp.org/papers/main)
Interpretation of NLP models through input marginalization
Comments 10 pages, 5 figures, to be published in the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)
Improving Limited Labeled Dialogue State Tracking with Self-Supervision
Comments EMNLP 2020 (findings)
Probing Task-Oriented Dialogue Representation from Language Models
Comments EMNLP 2020
Word Frequency Does Not Predict Grammatical Knowledge in Language Models
Comments EMNLP 2020
PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction
Comments EMNLP 2020
X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models
Comments EMNLP 2020
Visually-Grounded Planning without Vision: Language Models Infer Detailed Plans from High-level Instructions
Comments Accepted to Findings of EMNLP. V2: corrected typo Table 1; margins Table 3
ETC: Encoding Long and Structured Inputs in Transformers
Comments Accepted at EMNLP 2020
Graph Transformer Networks with Syntactic and Semantic Structures for Event Argument Extraction
Comments accepted at EMNLP 2020 findings
Improving Aspect-based Sentiment Analysis with Gated Graph Convolutional Networks and Syntax-based Regulation
Comments accepted at EMNLP 2020 findings
FastFormers: Highly Efficient Transformer Models for Natural Language Understanding
Comments Accepted to SustaiNLP 2020 at EMNLP 2020
Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learning
Comments accepted at EMNLP 2020 main conference
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
Comments 19 pages, accepted by EMNLP 2020 main conference as a long paper. Code will be available at https://github.com/salesforce/DNNC-few-shot-intent
Improving Multilingual Models with Language-Clustered Vocabularies
Comments Published in the main conference of EMNLP 2020
Long Document Ranking with Query-Directed Sparse Transformer
Comments Accepted by EMNLP 2020, 12 pages, 5 figures
TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classification
Comments Findings of EMNLP 2020. TweetEval benchmark available at https://github.com/cardiffnlp/tweeteval
SIGTYP 2020 Shared Task: Prediction of Typological Features
Comments SigTyp 2020 Shared Task Description Paper @ EMNLP 2020
Are "Undocumented Workers" the Same as "Illegal Aliens"? Disentangling Denotation and Connotation in Vector Spaces
Comments Published at EMNLP 2020. Recorded talk available at https://youtu.be/V2pdS6Y_8n0 . Code and data available at https://github.com/awebson/congressional_adversary
A little goes a long way: Improving toxic language classification despite data scarcity
Comments To appear in Findings of ACL: EMNLP 2020
