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A large annotated corpus for learning natural language inference

A large annotated corpus for learning natural language inference

21 August 2015
Samuel R. Bowman
Gabor Angeli
Christopher Potts
Christopher D. Manning
ArXivPDFHTML

Papers citing "A large annotated corpus for learning natural language inference"

50 / 911 papers shown
Title
On the Cross-lingual Transferability of Monolingual Representations
On the Cross-lingual Transferability of Monolingual Representations
Mikel Artetxe
Sebastian Ruder
Dani Yogatama
33
780
0
25 Oct 2019
HUBERT Untangles BERT to Improve Transfer across NLP Tasks
HUBERT Untangles BERT to Improve Transfer across NLP Tasks
M. Moradshahi
Hamid Palangi
M. Lam
P. Smolensky
Jianfeng Gao
34
16
0
25 Oct 2019
Diversify Your Datasets: Analyzing Generalization via Controlled
  Variance in Adversarial Datasets
Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets
Ohad Rozen
Vered Shwartz
Roee Aharoni
Ido Dagan
AAML
21
37
0
21 Oct 2019
Discovering the Compositional Structure of Vector Representations with
  Role Learning Networks
Discovering the Compositional Structure of Vector Representations with Role Learning Networks
Paul Soulos
R. Thomas McCoy
Tal Linzen
P. Smolensky
CoGe
29
43
0
21 Oct 2019
Improving Sequence Modeling Ability of Recurrent Neural Networks via
  Sememes
Improving Sequence Modeling Ability of Recurrent Neural Networks via Sememes
Yujia Qin
Fanchao Qi
Sicong Ouyang
Zhiyuan Liu
Cheng Yang
Yasheng Wang
Qun Liu
Maosong Sun
28
5
0
20 Oct 2019
Universal Text Representation from BERT: An Empirical Study
Universal Text Representation from BERT: An Empirical Study
Xiaofei Ma
Zhiguo Wang
Patrick Ng
Ramesh Nallapati
Bing Xiang
OOD
24
66
0
17 Oct 2019
BERT for Evidence Retrieval and Claim Verification
BERT for Evidence Retrieval and Claim Verification
Shrishti Saha Shetu
Christof Monz
E. Mabande
RALM
23
120
0
07 Oct 2019
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods
Can I Trust the Explainer? Verifying Post-hoc Explanatory Methods
Oana-Maria Camburu
Eleonora Giunchiglia
Jakob N. Foerster
Thomas Lukasiewicz
Phil Blunsom
FAtt
AAML
34
60
0
04 Oct 2019
Learning the Difference that Makes a Difference with
  Counterfactually-Augmented Data
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data
Divyansh Kaushik
Eduard H. Hovy
Zachary Chase Lipton
CML
28
562
0
26 Sep 2019
On Model Stability as a Function of Random Seed
On Model Stability as a Function of Random Seed
Pranava Madhyastha
Dhruv Batra
45
62
0
23 Sep 2019
Text Length Adaptation in Sentiment Classification
Text Length Adaptation in Sentiment Classification
Reinald Kim Amplayo
Seonjae Lim
Seung-won Hwang
VLM
28
5
0
18 Sep 2019
Improving Natural Language Inference with a Pretrained Parser
Improving Natural Language Inference with a Pretrained Parser
D. Pang
Lucy H. Lin
Noah A. Smith
25
14
0
18 Sep 2019
Revealing the Importance of Semantic Retrieval for Machine Reading at
  Scale
Revealing the Importance of Semantic Retrieval for Machine Reading at Scale
Yixin Nie
Songhe Wang
Joey Tianyi Zhou
RALM
164
134
0
17 Sep 2019
Probing Natural Language Inference Models through Semantic Fragments
Probing Natural Language Inference Models through Semantic Fragments
Kyle Richardson
Hai Hu
L. Moss
Ashish Sabharwal
19
148
0
16 Sep 2019
A Bayesian Approach to Direct and Inverse Abstract Argumentation
  Problems
A Bayesian Approach to Direct and Inverse Abstract Argumentation Problems
Hiroyuki Kido
B. Liao
AAML
20
5
0
10 Sep 2019
Supervised Multimodal Bitransformers for Classifying Images and Text
Supervised Multimodal Bitransformers for Classifying Images and Text
Douwe Kiela
Suvrat Bhooshan
Hamed Firooz
Ethan Perez
Davide Testuggine
59
242
0
06 Sep 2019
Semantics-aware BERT for Language Understanding
Semantics-aware BERT for Language Understanding
Zhuosheng Zhang
Yuwei Wu
Zhao Hai
Z. Li
Shuailiang Zhang
Xi Zhou
Xiang Zhou
21
365
0
05 Sep 2019
Better Rewards Yield Better Summaries: Learning to Summarise Without
  References
Better Rewards Yield Better Summaries: Learning to Summarise Without References
F. Böhm
Yang Gao
Christian M. Meyer
Ori Shapira
Ido Dagan
Iryna Gurevych
33
106
0
03 Sep 2019
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text
Bohan Li
Junxian He
Graham Neubig
Taylor Berg-Kirkpatrick
Yiming Yang
DRL
13
70
0
02 Sep 2019
A Logic-Driven Framework for Consistency of Neural Models
A Logic-Driven Framework for Consistency of Neural Models
Tao Li
Vivek Gupta
Maitrey Mehta
Vivek Srikumar
AI4CE
29
101
0
31 Aug 2019
Autoregressive Text Generation Beyond Feedback Loops
Autoregressive Text Generation Beyond Feedback Loops
Florian Schmidt
Stephan Mandt
Thomas Hofmann
AI4TS
20
14
0
30 Aug 2019
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
Nils Reimers
Iryna Gurevych
105
11,789
0
27 Aug 2019
On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model
  Compression
On the Effectiveness of Low-Rank Matrix Factorization for LSTM Model Compression
Genta Indra Winata
Andrea Madotto
Jamin Shin
Elham J. Barezi
Pascale Fung
27
28
0
27 Aug 2019
Denoising based Sequence-to-Sequence Pre-training for Text Generation
Denoising based Sequence-to-Sequence Pre-training for Text Generation
Liang Wang
Wei Zhao
Ruoyu Jia
Sujian Li
Jingming Liu
VLM
AI4CE
42
37
0
22 Aug 2019
Are We Modeling the Task or the Annotator? An Investigation of Annotator
  Bias in Natural Language Understanding Datasets
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets
Mor Geva
Yoav Goldberg
Jonathan Berant
242
321
0
21 Aug 2019
Similarity Learning for Authorship Verification in Social Media
Similarity Learning for Authorship Verification in Social Media
Benedikt T. Boenninghoff
R. M. Nickel
Steffen Zeiler
D. Kolossa
33
42
0
20 Aug 2019
Universal Adversarial Triggers for Attacking and Analyzing NLP
Universal Adversarial Triggers for Attacking and Analyzing NLP
Eric Wallace
Shi Feng
Nikhil Kandpal
Matt Gardner
Sameer Singh
AAML
SILM
60
842
0
20 Aug 2019
Style Transfer for Texts: Retrain, Report Errors, Compare with Rewrites
Style Transfer for Texts: Retrain, Report Errors, Compare with Rewrites
Alexey Tikhonov
Viacheslav Shibaev
Aleksander Nagaev
Aigul Nugmanova
Ivan P. Yamshchikov
31
37
0
19 Aug 2019
Align, Mask and Select: A Simple Method for Incorporating Commonsense
  Knowledge into Language Representation Models
Align, Mask and Select: A Simple Method for Incorporating Commonsense Knowledge into Language Representation Models
Zhiquan Ye
Qian Chen
Wen Wang
Zhenhua Ling
27
68
0
19 Aug 2019
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text
Koustuv Sinha
Shagun Sodhani
Jin Dong
Joelle Pineau
William L. Hamilton
32
201
0
16 Aug 2019
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal
  Pre-training
Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training
Gen Li
Nan Duan
Yuejian Fang
Ming Gong
Daxin Jiang
Ming Zhou
SSL
VLM
MLLM
89
895
0
16 Aug 2019
Reasoning Over Paragraph Effects in Situations
Reasoning Over Paragraph Effects in Situations
Kevin Lin
Oyvind Tafjord
Peter Clark
Matt Gardner
20
115
0
16 Aug 2019
Towards Debiasing Fact Verification Models
Towards Debiasing Fact Verification Models
Tal Schuster
Darsh J. Shah
Yun Jie Serene Yeo
Daniel Filizzola
Enrico Santus
Regina Barzilay
36
209
0
14 Aug 2019
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence
  Embedding
Scalable Attentive Sentence-Pair Modeling via Distilled Sentence Embedding
Oren Barkan
Noam Razin
Itzik Malkiel
Ori Katz
Avi Caciularu
Noam Koenigstein
FedML
41
37
0
14 Aug 2019
DropAttention: A Regularization Method for Fully-Connected
  Self-Attention Networks
DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks
Zehui Lin
Pengfei Liu
Luyao Huang
Junkun Chen
Xipeng Qiu
Xuanjing Huang
3DPC
16
44
0
25 Jul 2019
Trends in Integration of Vision and Language Research: A Survey of
  Tasks, Datasets, and Methods
Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
Aditya Mogadala
M. Kalimuthu
Dietrich Klakow
VLM
29
133
0
22 Jul 2019
GEAR: Graph-based Evidence Aggregating and Reasoning for Fact
  Verification
GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification
Jie Zhou
Xu Han
Cheng Yang
Zhiyuan Liu
Lifeng Wang
Changcheng Li
Maosong Sun
24
198
0
22 Jul 2019
Probing Neural Network Comprehension of Natural Language Arguments
Probing Neural Network Comprehension of Natural Language Arguments
Timothy Niven
Hung-Yu kao
AAML
45
453
0
17 Jul 2019
Fake News Detection as Natural Language Inference
Fake News Detection as Natural Language Inference
Kai-Chou Yang
Timothy Niven
Hung-Yu kao
18
35
0
17 Jul 2019
On Adversarial Removal of Hypothesis-only Bias in Natural Language
  Inference
On Adversarial Removal of Hypothesis-only Bias in Natural Language Inference
Yonatan Belinkov
Adam Poliak
Stuart M. Shieber
Benjamin Van Durme
Alexander M. Rush
AAML
45
69
0
09 Jul 2019
Don't Take the Premise for Granted: Mitigating Artifacts in Natural
  Language Inference
Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference
Yonatan Belinkov
Adam Poliak
Stuart M. Shieber
Benjamin Van Durme
Alexander M. Rush
29
94
0
09 Jul 2019
Machine Learning Testing: Survey, Landscapes and Horizons
Machine Learning Testing: Survey, Landscapes and Horizons
Jie M. Zhang
Mark Harman
Lei Ma
Yang Liu
VLM
AILaw
39
741
0
19 Jun 2019
Learning Compressed Sentence Representations for On-Device Text
  Processing
Learning Compressed Sentence Representations for On-Device Text Processing
Dinghan Shen
Pengyu Cheng
Dhanasekar Sundararaman
Xinyuan Zhang
Qian Yang
Meng Tang
Asli Celikyilmaz
Lawrence Carin
18
22
0
19 Jun 2019
Multi-Level Matching and Aggregation Network for Few-Shot Relation
  Classification
Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
Zhiquan Ye
Zhenhua Ling
27
134
0
16 Jun 2019
Can neural networks understand monotonicity reasoning?
Can neural networks understand monotonicity reasoning?
Hitomi Yanaka
K. Mineshima
D. Bekki
Kentaro Inui
Satoshi Sekine
Lasha Abzianidze
Johan Bos
LRM
32
80
0
15 Jun 2019
Augmenting Neural Networks with First-order Logic
Augmenting Neural Networks with First-order Logic
Tao Li
Vivek Srikumar
16
109
0
14 Jun 2019
Lightweight and Efficient Neural Natural Language Processing with
  Quaternion Networks
Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks
Yi Tay
Aston Zhang
Anh Tuan Luu
J. Rao
Shuai Zhang
Shuohang Wang
Jie Fu
S. Hui
23
55
0
11 Jun 2019
Improving the Similarity Measure of Determinantal Point Processes for
  Extractive Multi-Document Summarization
Improving the Similarity Measure of Determinantal Point Processes for Extractive Multi-Document Summarization
Sangwoo Cho
Logan Lebanoff
H. Foroosh
Fei Liu
30
53
0
31 May 2019
Effective writing style imitation via combinatorial paraphrasing
Effective writing style imitation via combinatorial paraphrasing
Tommi Gröndahl
Nadarajah Asokan
18
7
0
31 May 2019
Threshold-Based Retrieval and Textual Entailment Detection on Legal Bar
  Exam Questions
Threshold-Based Retrieval and Textual Entailment Detection on Legal Bar Exam Questions
Sabine Wehnert
Sayed Anisul Hoque
W. Fenske
G. Saake
ELM
AILaw
20
14
0
30 May 2019
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