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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 / 927 papers shown
Title
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP
  Tasks
KNOT: Knowledge Distillation using Optimal Transport for Solving NLP Tasks
Rishabh Bhardwaj
Tushar Vaidya
Soujanya Poria
OT
FedML
70
7
0
06 Oct 2021
Investigating the Impact of Pre-trained Language Models on Dialog
  Evaluation
Investigating the Impact of Pre-trained Language Models on Dialog Evaluation
Chen Zhang
L. F. D’Haro
Yiming Chen
Thomas Friedrichs
Haizhou Li
23
5
0
05 Oct 2021
SlovakBERT: Slovak Masked Language Model
SlovakBERT: Slovak Masked Language Model
Matúš Pikuliak
Stefan Grivalsky
Martin Konopka
Miroslav Blšták
Martin Tamajka
Viktor Bachratý
Marian Simko
Pavol Balázik
Michal Trnka
Filip Uhlárik
37
27
0
30 Sep 2021
Trans-Encoder: Unsupervised sentence-pair modelling through self- and
  mutual-distillations
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations
Fangyu Liu
Yunlong Jiao
Jordan Massiah
Emine Yilmaz
Serhii Havrylov
SSL
97
29
0
27 Sep 2021
DialogueCSE: Dialogue-based Contrastive Learning of Sentence Embeddings
DialogueCSE: Dialogue-based Contrastive Learning of Sentence Embeddings
Che Liu
Rui Wang
Jinghua Liu
Jian Sun
Fei Huang
Luo Si
48
40
0
26 Sep 2021
MINIMAL: Mining Models for Data Free Universal Adversarial Triggers
MINIMAL: Mining Models for Data Free Universal Adversarial Triggers
Swapnil Parekh
Yaman Kumar Singla
Somesh Singh
Changyou Chen
Balaji Krishnamurthy
R. Shah
AAML
29
3
0
25 Sep 2021
Automated Fact-Checking: A Survey
Automated Fact-Checking: A Survey
Xia Zeng
Amani S. Abumansour
A. Zubiaga
HILM
195
96
0
23 Sep 2021
Incorporating Temporal Information in Entailment Graph Mining
Incorporating Temporal Information in Entailment Graph Mining
Liane Guillou
Sander Bijl de Vroe
Mohammad Javad Hosseini
Mark Johnson
Mark Steedman
135
10
0
20 Sep 2021
Training Dynamic based data filtering may not work for NLP datasets
Training Dynamic based data filtering may not work for NLP datasets
Arka Talukdar
Monika Dagar
Prachi Gupta
Varun G. Menon
NoLa
50
3
0
19 Sep 2021
Knowledge-Enhanced Evidence Retrieval for Counterargument Generation
Knowledge-Enhanced Evidence Retrieval for Counterargument Generation
Yohan Jo
Haneul Yoo
Jinyeong Bak
Alice Oh
Chris Reed
Eduard H. Hovy
RALM
45
12
0
19 Sep 2021
Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic
Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic
Zijun Wu
Zi Xuan Zhang
Atharva Naik
Zhijian Mei
Mauajama Firdaus
Lili Mou
LRM
NAI
49
14
0
18 Sep 2021
Towards Handling Unconstrained User Preferences in Dialogue
Towards Handling Unconstrained User Preferences in Dialogue
S. Pandey
Svetlana Stoyanchev
R. Doddipatla
19
2
0
17 Sep 2021
Let the CAT out of the bag: Contrastive Attributed explanations for Text
Let the CAT out of the bag: Contrastive Attributed explanations for Text
Saneem A. Chemmengath
A. Azad
Ronny Luss
Amit Dhurandhar
FAtt
34
10
0
16 Sep 2021
Does External Knowledge Help Explainable Natural Language Inference?
  Automatic Evaluation vs. Human Ratings
Does External Knowledge Help Explainable Natural Language Inference? Automatic Evaluation vs. Human Ratings
Hendrik Schuff
Hsiu-yu Yang
Heike Adel
Ngoc Thang Vu
ELM
ReLM
LRM
49
13
0
16 Sep 2021
On the Language-specificity of Multilingual BERT and the Impact of
  Fine-tuning
On the Language-specificity of Multilingual BERT and the Impact of Fine-tuning
Marc Tanti
Lonneke van der Plas
Claudia Borg
Albert Gatt
25
10
0
14 Sep 2021
A Temporal Variational Model for Story Generation
A Temporal Variational Model for Story Generation
David Wilmot
Frank Keller
DRL
40
8
0
14 Sep 2021
KFCNet: Knowledge Filtering and Contrastive Learning Network for
  Generative Commonsense Reasoning
KFCNet: Knowledge Filtering and Contrastive Learning Network for Generative Commonsense Reasoning
Haonan Li
Yeyun Gong
Jian Jiao
Ruofei Zhang
Timothy Baldwin
Nan Duan
OffRL
60
6
0
14 Sep 2021
Identifying Untrustworthy Samples: Data Filtering for Open-domain
  Dialogues with Bayesian Optimization
Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
Lei Shen
Haolan Zhan
Xin Shen
Hongshen Chen
Xiaofang Zhao
Xiao-Dan Zhu
47
17
0
14 Sep 2021
STraTA: Self-Training with Task Augmentation for Better Few-shot
  Learning
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning
Tu Vu
Minh-Thang Luong
Quoc V. Le
Grady Simon
Mohit Iyyer
131
61
0
13 Sep 2021
Raise a Child in Large Language Model: Towards Effective and
  Generalizable Fine-tuning
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
Runxin Xu
Fuli Luo
Zhiyuan Zhang
Chuanqi Tan
Baobao Chang
Songfang Huang
Fei Huang
LRM
151
178
0
13 Sep 2021
An Objective Metric for Explainable AI: How and Why to Estimate the
  Degree of Explainability
An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability
Francesco Sovrano
F. Vitali
45
30
0
11 Sep 2021
Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense
  Language Understanding
Tiered Reasoning for Intuitive Physics: Toward Verifiable Commonsense Language Understanding
Shane Storks
Qiaozi Gao
Yichi Zhang
J. Chai
ReLM
LRM
51
22
0
10 Sep 2021
A Strong Baseline for Query Efficient Attacks in a Black Box Setting
A Strong Baseline for Query Efficient Attacks in a Black Box Setting
Rishabh Maheshwary
Saket Maheshwary
Vikram Pudi
AAML
30
30
0
10 Sep 2021
Counterfactual Adversarial Learning with Representation Interpolation
Counterfactual Adversarial Learning with Representation Interpolation
Wen Wang
Wei Ping
Ning Shi
Jinfeng Li
Bingyu Zhu
Xiangyu Liu
Rongxin Zhang
AAML
OOD
CML
26
2
0
10 Sep 2021
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
Prasetya Ajie Utama
N. Moosavi
Victor Sanh
Iryna Gurevych
AAML
68
35
0
09 Sep 2021
Debiasing Methods in Natural Language Understanding Make Bias More
  Accessible
Debiasing Methods in Natural Language Understanding Make Bias More Accessible
Michael J. Mendelson
Yonatan Belinkov
45
23
0
09 Sep 2021
Unsupervised Pre-training with Structured Knowledge for Improving
  Natural Language Inference
Unsupervised Pre-training with Structured Knowledge for Improving Natural Language Inference
Xiaoyu Yang
Xiao-Dan Zhu
Zhan Shi
Tianda Li
SSL
27
1
0
08 Sep 2021
Discrete and Soft Prompting for Multilingual Models
Discrete and Soft Prompting for Multilingual Models
Mengjie Zhao
Hinrich Schütze
LRM
18
71
0
08 Sep 2021
NSP-BERT: A Prompt-based Few-Shot Learner Through an Original
  Pre-training Task--Next Sentence Prediction
NSP-BERT: A Prompt-based Few-Shot Learner Through an Original Pre-training Task--Next Sentence Prediction
Yi Sun
Yu Zheng
Chao Hao
Hangping Qiu
VLM
43
37
0
08 Sep 2021
Automated Robustness with Adversarial Training as a Post-Processing Step
Automated Robustness with Adversarial Training as a Post-Processing Step
Ambrish Rawat
M. Sinn
Beat Buesser
AAML
19
0
0
06 Sep 2021
Finetuned Language Models Are Zero-Shot Learners
Finetuned Language Models Are Zero-Shot Learners
Jason W. Wei
Maarten Bosma
Vincent Zhao
Kelvin Guu
Adams Wei Yu
Brian Lester
Nan Du
Andrew M. Dai
Quoc V. Le
ALM
UQCV
40
3,600
0
03 Sep 2021
Detecting Speaker Personas from Conversational Texts
Detecting Speaker Personas from Conversational Texts
Jia-Chen Gu
Zhen-Hua Ling
Yu-Huan Wu
Quan Liu
Zhigang Chen
Xiao-Dan Zhu
24
16
0
03 Sep 2021
Aligning Cross-lingual Sentence Representations with Dual Momentum
  Contrast
Aligning Cross-lingual Sentence Representations with Dual Momentum Contrast
Liang Wang
Wei Zhao
Jingming Liu
40
14
0
01 Sep 2021
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language
  Representations
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations
Hang Li
Yunxing Kang
Tianqiao Liu
Wenbiao Ding
Zitao Liu
41
17
0
01 Sep 2021
Sentence Bottleneck Autoencoders from Transformer Language Models
Sentence Bottleneck Autoencoders from Transformer Language Models
Ivan Montero
Nikolaos Pappas
Noah A. Smith
AI4CE
25
28
0
31 Aug 2021
Are Training Resources Insufficient? Predict First Then Explain!
Are Training Resources Insufficient? Predict First Then Explain!
Myeongjun Jang
Thomas Lukasiewicz
LRM
26
7
0
29 Aug 2021
Layer-wise Model Pruning based on Mutual Information
Layer-wise Model Pruning based on Mutual Information
Chun Fan
Jiwei Li
Xiang Ao
Fei Wu
Yuxian Meng
Xiaofei Sun
50
19
0
28 Aug 2021
A Survey on Automated Fact-Checking
A Survey on Automated Fact-Checking
Zhijiang Guo
M. Schlichtkrull
Andreas Vlachos
36
463
0
26 Aug 2021
Just Say No: Analyzing the Stance of Neural Dialogue Generation in
  Offensive Contexts
Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts
Ashutosh Baheti
Maarten Sap
Alan Ritter
Mark O. Riedl
26
85
0
26 Aug 2021
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
Zirui Wang
Jiahui Yu
Adams Wei Yu
Zihang Dai
Yulia Tsvetkov
Yuan Cao
VLM
MLLM
51
782
0
24 Aug 2021
Regularizing Transformers With Deep Probabilistic Layers
Regularizing Transformers With Deep Probabilistic Layers
Aurora Cobo Aguilera
Pablo Martínez Olmos
Antonio Artés-Rodríguez
Fernando Pérez-Cruz
41
7
0
23 Aug 2021
Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text
  Models
Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models
Jianmo Ni
Gustavo Hernández Ábrego
Noah Constant
Ji Ma
Keith B. Hall
Daniel Cer
Yinfei Yang
63
532
0
19 Aug 2021
From LSAT: The Progress and Challenges of Complex Reasoning
From LSAT: The Progress and Challenges of Complex Reasoning
Siyuan Wang
Zhongkun Liu
Wanjun Zhong
Ming Zhou
Zhongyu Wei
Zhumin Chen
Nan Duan
ELM
38
44
0
02 Aug 2021
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods
  in Natural Language Processing
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
Pengfei Liu
Weizhe Yuan
Jinlan Fu
Zhengbao Jiang
Hiroaki Hayashi
Graham Neubig
VLM
SyDa
114
3,858
0
28 Jul 2021
Towards Robustness Against Natural Language Word Substitutions
Towards Robustness Against Natural Language Word Substitutions
Xinshuai Dong
Anh Tuan Luu
Rongrong Ji
Hong Liu
SILM
AAML
38
113
0
28 Jul 2021
Improved Text Classification via Contrastive Adversarial Training
Improved Text Classification via Contrastive Adversarial Training
Lin Pan
Chung-Wei Hang
Avirup Sil
Saloni Potdar
AAML
33
86
0
21 Jul 2021
Generative Pretraining for Paraphrase Evaluation
Generative Pretraining for Paraphrase Evaluation
J. Weston
R. Lenain
U. Meepegama
E. Fristed
AIMat
27
10
0
17 Jul 2021
Align before Fuse: Vision and Language Representation Learning with
  Momentum Distillation
Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
Junnan Li
Ramprasaath R. Selvaraju
Akhilesh Deepak Gotmare
Chenyu You
Caiming Xiong
Guosheng Lin
FaML
88
1,893
0
16 Jul 2021
FLEX: Unifying Evaluation for Few-Shot NLP
FLEX: Unifying Evaluation for Few-Shot NLP
Jonathan Bragg
Arman Cohan
Kyle Lo
Iz Beltagy
208
104
0
15 Jul 2021
Uncertainty-Aware Reliable Text Classification
Uncertainty-Aware Reliable Text Classification
Yibo Hu
Latifur Khan
EDL
UQCV
40
33
0
15 Jul 2021
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