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EMNLP
Member since:
2020-12-20
Last seen:
2020-12-20
User details
Name:
Conference on Empirical Methods in Natural Language Processing
Affiliation:
Association for Computational Linguistics
Website:
https://2020.emnlp.org/
About me:
The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) invites the submission of long and short papers on substantial, original, and unpublished research in empirical methods for Natural Language Processing.
Papertalks of EMNLP
16/11/2020
Interpretation of NLP models through input marginalization
Siwon Kim
,
Jihun Yi
,
Eunji Kim
,
Sungroh Yoon
Keywords
Abstract
Paper
nlp
,
out-of-distribution problem
,
sentiment analysis
,
natural inference
10:01
16/11/2020
An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction
Bhargavi Paranjape
,
Mandar Joshi
,
John Thickstun
and
Hannaneh Hajishirzi
,
Luke Zettlemoyer
Keywords
Abstract
Paper
language understanding
,
semi-supervised setting
,
complex models
,
explainer
11:44
16/11/2020
Coarse-to-Fine Pre-training for Named Entity Recognition
Xue Mengge
,
Bowen Yu
,
Zhenyu Zhang
and
Tingwen Liu
,
Yue Zhang
,
Bin Wang
Keywords
Abstract
Paper
named recognition
,
bert
,
en-tity task
,
pre-trainingapproaches
9:23
16/11/2020
Distilling Multiple Domains for Neural Machine Translation
Anna Currey
,
Prashant Mathur
,
Georgiana Dinu
Keywords
Abstract
Paper
translation
,
neural translation
,
multi-domain model
,
high-resource conditions
12:15
16/11/2020
On the importance of pre-training data volume for compact language models
Vincent Micheli
,
Martin d'Hoffschmidt
,
François Fleuret
Keywords
Abstract
Paper
language modeling
,
sustainable practices
,
compact models
,
multiple models
6:51
16/11/2020
A Time-Aware Transformer Based Model for Suicide Ideation Detection on Social Media
Ramit Sawhney
,
Harshit Joshi
,
Saumya Gandhi
,
Rajiv Ratn Shah
Keywords
Abstract
Paper
identification users
,
suicide prevention
,
suicide ideation
,
screening risk
11:20
16/11/2020
Training Question Answering Models From Synthetic Data
Raul Puri
,
Ryan Spring
,
Mohammad Shoeybi
and
Mostofa Patwary
,
Bryan Catanzaro
Keywords
Abstract
Paper
question generation
,
squad task
,
em
,
data method
11:33
16/11/2020
DagoBERT: Generating Derivational Morphology with a Pretrained Language Model
Valentin Hofmann
,
Janet Pierrehumbert
,
Hinrich Schütze
Keywords
Abstract
Paper
full finetuning
,
derivation generation
,
pretrained models
,
plms
10:15
16/11/2020
Losing Heads in the Lottery: Pruning Transformer Attention in Neural Machine Translation
Maximiliana Behnke
,
Kenneth Heafield
Keywords
Abstract
Paper
machine translation
,
inference
,
attention mechanism
,
transformer architecture
10:09
16/11/2020
Bridging Linguistic Typology and Multilingual Machine Translation with Multi-View Language Representations
Arturo Oncevay
,
Barry Haddow
,
Alexandra Birch
Keywords
Abstract
Paper
multilingual translation
,
language clustering
,
multilingual transfer
,
singular analysis
11:28
16/11/2020
Embedding Words in Non-Vector Space with Unsupervised Graph Learning
Max Ryabinin
,
Sergei Popov
,
Liudmila Prokhorenkova
,
Elena Voita
Keywords
Abstract
Paper
word tasks
,
word embeddings
,
graphglove
,
unsupervised representations
11:04
16/11/2020
Predicting Reference: What do Language Models Learn about Discourse Models?
Shiva Upadhye
,
Leon Bergen
,
Andrew Kehler
Keywords
Abstract
Paper
neural models
,
grammatical knowledge
,
referential biases
,
discourse ability
6:41
16/11/2020
Evaluating the Factual Consistency of Abstractive Text Summarization
Wojciech Kryscinski
,
Bryan McCann
,
Caiming Xiong
,
Richard Socher
Keywords
Abstract
Paper
assessing algorithms
,
natural inference
,
fact checking
,
auxiliary tasks
12:05
16/11/2020
Friendly Topic Assistant for Transformer Based Abstractive Summarization
Zhengjue Wang
,
Zhibin Duan
,
Hao Zhang
and
Chaojie Wang
,
Long Tian
,
Bo Chen
,
Mingyuan Zhou
Keywords
Abstract
Paper
abstractive summarization
,
document understanding
,
summary generation
,
ta
10:21
16/11/2020
A Method for Building a Commonsense Inference Dataset based on Basic Events
Kazumasa Omura
,
Daisuke Kawahara
,
Sadao Kurohashi
Keywords
Abstract
Paper
automatic extraction
,
language research
,
crowdsourcing
,
transfer model
11:35
16/11/2020
Generationary or “How We Went beyond Word Sense Inventories and Learned to Gloss”
Michele Bevilacqua
,
Marco Maru
,
Roberto Navigli
Keywords
Abstract
Paper
generative modeling
,
definition modeling
,
discriminative tasks
,
word disambiguation
11:49
16/11/2020
Conversational Document Prediction to Assist Customer Care Agents
Jatin Ganhotra
,
Haggai Roitman
,
Doron Cohen
and
Nathaniel Mills
,
Chulaka Gunasekara
,
Yosi Mass
,
Sachindra Joshi
,
Luis Lastras
,
David Konopnicki
Keywords
Abstract
Paper
customer conversations
,
predicting documents
,
customer agents
,
information models
6:38
16/11/2020
Word Rotator's Distance
Sho Yokoi
,
Ryo Takahashi
,
Reina Akama
and
Jun Suzuki
,
Kentaro Inui
Keywords
Abstract
Paper
assessing similarity
,
vector converter
,
word alignment
,
alignment-based approaches
11:32
16/11/2020
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference
Jianguo Zhang
,
Kazuma Hashimoto
,
Wenhao Liu
and
Chien-Sheng Wu
,
Yao Wan
,
Philip Yu
,
Richard Socher
,
Caiming Xiong
Keywords
Abstract
Paper
intent detection
,
detecting intents
,
oos detection
,
large-scale task
11:43
16/11/2020
Multi-View Sequence-to-Sequence Models with Conversational Structure for Abstractive Dialogue Summarization
Jiaao Chen
,
Diyi Yang
Keywords
Abstract
Paper
text summarization
,
nlp
,
summarizing text
,
human-humanmachine interaction
12:02
16/11/2020
Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation
Jason Lee
,
Raphael Shu
,
Kyunghyun Cho
Keywords
Abstract
Paper
non-autoregressive translation
,
translation
,
machine translation
,
inference procedure
11:44
16/11/2020
Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks
Denis Emelin
,
Ivan Titov
,
Rico Sennrich
Keywords
Abstract
Paper
word disambiguation
,
nmt
,
prediction errors
,
adversarial strategy
12:57
16/11/2020
Imitation Attacks and Defenses for Black-box Machine Translation Systems
Eric Wallace
,
Mitchell Stern
,
Dawn Song
Keywords
Abstract
Paper
machine mt
,
machine
,
mt
,
production systems
12:25
16/11/2020
Tell Me How to Ask Again: Question Data Augmentation with Controllable Rewriting in Continuous Space
Dayiheng Liu
,
Yeyun Gong
,
Jie Fu
and
Yu Yan
,
Jiusheng Chen
,
Jiancheng Lv
,
Nan Duan
,
Ming Zhou
Keywords
Abstract
Paper
machine comprehension
,
question generation
,
question-answering tasks
,
question task
10:42
16/11/2020
Unsupervised Question Decomposition for Question Answering
Ethan Perez
,
Patrick Lewis
,
Wen-tau Yih
and
Kyunghyun Cho
,
Douwe Kiela
Keywords
Abstract
Paper
question qa
,
labeling questions
,
one-to-n transduction
,
qa
12:04
16/11/2020
Inference Strategies for Machine Translation with Conditional Masking
Julia Kreutzer
,
George Foster
,
Colin Cherry
Keywords
Abstract
Paper
non-autoregressive tasks
,
machine translation
,
masked inference
,
machine tasks
6:36
16/11/2020
Learning Music Helps You Read: Using Transfer to Study Linguistic Structure in Language Models
Isabel Papadimitriou
,
Dan Jurafsky
Keywords
Abstract
Paper
analyzing structure
,
encoding structure
,
natural acquisition
,
transfer learning
11:44
16/11/2020
Scalable Zero-shot Entity Linking with Dense Entity Retrieval
Ledell Wu
,
Fabio Petroni
,
Martin Josifoski
and
Sebastian Riedel
,
Luke Zettlemoyer
Keywords
Abstract
Paper
retrieval
,
non-zero-shot evaluations
,
bi-encoder linking
,
bert-based model
11:37
16/11/2020
Dialogue Response Ranking Training with Large-Scale Human Feedback Data
Xiang Gao
,
Yizhe Zhang
,
Michel Galley
and
Chris Brockett
,
Bill Dolan
Keywords
Abstract
Paper
feedback prediction
,
ranking problem
,
predicting feedback
,
open-domain models
11:57
16/11/2020
With More Contexts Comes Better Performance: Contextualized Sense Embeddings for All-Round Word Sense Disambiguation
Bianca Scarlini
,
Tommaso Pasini
,
Roberto Navigli
Keywords
Abstract
Paper
natural processing
,
english task
,
word-in-context task
,
contextualized embeddings
12:11
16/11/2020
Context-Aware Answer Extraction in Question Answering
Yeon Seonwoo
,
Ji-Hoon Kim
,
Jung-Woo Ha
,
Alice Oh
Keywords
Abstract
Paper
context prediction
,
context task
,
reading comprehension
,
extractive models
9:34
16/11/2020
An Empirical Study on Large-Scale Multi-Label Text Classification Including Few and Zero-Shot Labels
Ilias Chalkidis
,
Manos Fergadiotis
,
Sotiris Kotitsas
and
Prodromos Malakasiotis
,
Nikolaos Aletras
,
Ion Androutsopoulos
Keywords
Abstract
Paper
flat classification
,
hierarchical approaches
,
zero-shot learning
,
few learning
12:21
16/11/2020
OCR Post Correction for Endangered Language Texts
Shruti Rijhwani
,
Antonios Anastasopoulos
,
Graham Neubig
Keywords
Abstract
Paper
natural models
,
general-purpose tools
,
ocr method
,
recognition rate
13:32
16/11/2020
On the Ability and Limitations of Transformers to Recognize Formal Languages
Satwik Bhattamishra
,
Kabir Ahuja
,
Navin Goyal
Keywords
Abstract
Paper
nlp tasks
,
construction
,
transformers
,
lstms
11:27
16/11/2020
Extracting Implicitly Asserted Propositions in Argumentation
Yohan Jo
,
Jacky Visser
,
Chris Reed
,
Eduard Hovy
Keywords
Abstract
Paper
argumentation
,
imperatives argumentation
,
argument mining
,
rhetorical tools
11:17
16/11/2020
Why Skip If You Can Combine: A Simple Knowledge Distillation Technique for Intermediate Layers
Yimeng Wu
,
Peyman Passban
,
Mehdi Rezagholizadeh
,
Qun Liu
Keywords
Abstract
Paper
knowledge distillation
,
neural models
,
knowledge kd
,
kd
6:41
16/11/2020
We Can Detect Your Bias: Predicting the Political Ideology of News Articles
Ramy Baly
,
Giovanni Da San Martino
,
James Glass
,
Preslav Nakov
Keywords
Abstract
Paper
article-level prediction
,
adversarial adaptation
,
pre-trained transformers
,
leading ideology
11:55
16/11/2020
Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting
Sanyuan Chen
,
Yutai Hou
,
Yiming Cui
and
Wanxiang Che
,
Ting Liu
,
Xiangzhan Yu
Keywords
Abstract
Paper
pretraining
,
pretraining tasks
,
learning tasks
,
fine-tuning bert-large
10:52
16/11/2020
Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
Leonardo F. R. Ribeiro
,
Yue Zhang
,
Claire Gardent
,
Iryna Gurevych
Keywords
Abstract
Paper
graph-to-text models
,
global aggregation
,
node representations
,
global encoding
10:40
16/11/2020
MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models
Peng Xu
,
Mostofa Patwary
,
Mohammad Shoeybi
and
Raul Puri
,
Pascale Fung
,
Anima Anandkumar
,
Bryan Catanzaro
Keywords
Abstract
Paper
text generation
,
pre-trained models
,
megatron-cntrl
,
large-scale models
11:59
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