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Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural
  Language Inference

Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference

4 February 2019
R. Thomas McCoy
Ellie Pavlick
Tal Linzen
ArXivPDFHTML

Papers citing "Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference"

50 / 329 papers shown
Title
Leveraging the Inductive Bias of Large Language Models for Abstract
  Textual Reasoning
Leveraging the Inductive Bias of Large Language Models for Abstract Textual Reasoning
Christopher Rytting
David Wingate
AI4CE
LRM
13
26
0
05 Oct 2021
Separating Retention from Extraction in the Evaluation of End-to-end
  Relation Extraction
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction
Bruno Taillé
Vincent Guigue
Geoffrey Scoutheeten
Patrick Gallinari
79
5
0
24 Sep 2021
RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation
RAIL-KD: RAndom Intermediate Layer Mapping for Knowledge Distillation
Md. Akmal Haidar
Nithin Anchuri
Mehdi Rezagholizadeh
Abbas Ghaddar
Philippe Langlais
Pascal Poupart
31
22
0
21 Sep 2021
KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language
  Models via Knowledge Distillation
KroneckerBERT: Learning Kronecker Decomposition for Pre-trained Language Models via Knowledge Distillation
Marzieh S. Tahaei
Ella Charlaix
V. Nia
A. Ghodsi
Mehdi Rezagholizadeh
46
22
0
13 Sep 2021
The Grammar-Learning Trajectories of Neural Language Models
The Grammar-Learning Trajectories of Neural Language Models
Leshem Choshen
Guy Hacohen
D. Weinshall
Omri Abend
29
28
0
13 Sep 2021
Adversarial Examples for Evaluating Math Word Problem Solvers
Adversarial Examples for Evaluating Math Word Problem Solvers
Vivek Kumar
Rishabh Maheshwary
Vikram Pudi
AAML
30
33
0
13 Sep 2021
How to Select One Among All? An Extensive Empirical Study Towards the
  Robustness of Knowledge Distillation in Natural Language Understanding
How to Select One Among All? An Extensive Empirical Study Towards the Robustness of Knowledge Distillation in Natural Language Understanding
Tianda Li
Ahmad Rashid
A. Jafari
Pranav Sharma
A. Ghodsi
Mehdi Rezagholizadeh
AAML
33
5
0
13 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
49
22
0
10 Sep 2021
Studying word order through iterative shuffling
Studying word order through iterative shuffling
Nikolay Malkin
Sameera Lanka
Pranav Goel
Nebojsa Jojic
31
14
0
10 Sep 2021
An Evaluation Dataset and Strategy for Building Robust Multi-turn
  Response Selection Model
An Evaluation Dataset and Strategy for Building Robust Multi-turn Response Selection Model
Kijong Han
Seojin Lee
Wooin Lee
Joosung Lee
Donghun Lee
AAML
25
5
0
10 Sep 2021
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with
  Auxiliary Trigger Extraction
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction
Dong-Ho Lee
Ravi Kiran Selvam
Sheikh Muhammad Sarwar
Bill Yuchen Lin
Fred Morstatter
Jay Pujara
Elizabeth Boschee
James Allan
Xiang Ren
31
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
61
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
42
23
0
09 Sep 2021
End-to-End Self-Debiasing Framework for Robust NLU Training
End-to-End Self-Debiasing Framework for Robust NLU Training
Abbas Ghaddar
Philippe Langlais
Mehdi Rezagholizadeh
Ahmad Rashid
UQCV
34
36
0
05 Sep 2021
Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Do Prompt-Based Models Really Understand the Meaning of their Prompts?
Albert Webson
Ellie Pavlick
LRM
53
355
0
02 Sep 2021
Causal Inference in Natural Language Processing: Estimation, Prediction,
  Interpretation and Beyond
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond
Amir Feder
Katherine A. Keith
Emaad A. Manzoor
Reid Pryzant
Dhanya Sridhar
...
Roi Reichart
Margaret E. Roberts
Brandon M Stewart
Victor Veitch
Diyi Yang
CML
41
234
0
02 Sep 2021
How Does Adversarial Fine-Tuning Benefit BERT?
How Does Adversarial Fine-Tuning Benefit BERT?
J. Ebrahimi
Hao Yang
Wei Zhang
AAML
26
4
0
31 Aug 2021
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation
Lijie Wang
Hao Liu
Shu-ping Peng
Hongxuan Tang
Xinyan Xiao
Ying-Cong Chen
Hua Wu
Haifeng Wang
25
5
0
30 Aug 2021
Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot
  Event Classification
Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot Event Classification
Peiyi Wang
Runxin Xu
Tianyu Liu
Damai Dai
Baobao Chang
Zhifang Sui
27
16
0
29 Aug 2021
NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task
  Models
NoiER: An Approach for Training more Reliable Fine-TunedDownstream Task Models
Myeongjun Jang
Thomas Lukasiewicz
24
4
0
29 Aug 2021
Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive
  Text Summarization
Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization
Chujie Zheng
Kunpeng Zhang
Harry J. Wang
Ling Fan
Zhe Wang
25
6
0
26 Aug 2021
A Survey on Automated Fact-Checking
A Survey on Automated Fact-Checking
Zhijiang Guo
M. Schlichtkrull
Andreas Vlachos
27
459
0
26 Aug 2021
Underreporting of errors in NLG output, and what to do about it
Underreporting of errors in NLG output, and what to do about it
Emiel van Miltenburg
Miruna Clinciu
Ondrej Dusek
Dimitra Gkatzia
Stephanie Inglis
...
Saad Mahamood
Emma Manning
S. Schoch
Craig Thomson
Luou Wen
27
38
0
02 Aug 2021
Context-aware Adversarial Training for Name Regularity Bias in Named
  Entity Recognition
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition
Abbas Ghaddar
Philippe Langlais
Ahmad Rashid
Mehdi Rezagholizadeh
39
42
0
24 Jul 2021
CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with
  Minimal Supervision
CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision
Zhongyang Li
Xiao Ding
Kuo Liao
Bing Qin
Ting Liu
CML
29
17
0
21 Jul 2021
Trusting RoBERTa over BERT: Insights from CheckListing the Natural
  Language Inference Task
Trusting RoBERTa over BERT: Insights from CheckListing the Natural Language Inference Task
Ishan Tarunesh
Somak Aditya
Monojit Choudhury
15
17
0
15 Jul 2021
A Survey on Data Augmentation for Text Classification
A Survey on Data Augmentation for Text Classification
Markus Bayer
M. Kaufhold
Christian A. Reuter
36
336
0
07 Jul 2021
Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal
  Reasoning Models
Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models
Mingyue Han
Yinglin Wang
LRM
21
10
0
05 Jul 2021
An Investigation of the (In)effectiveness of Counterfactually Augmented
  Data
An Investigation of the (In)effectiveness of Counterfactually Augmented Data
Nitish Joshi
He He
OODD
19
46
0
01 Jul 2021
Mandoline: Model Evaluation under Distribution Shift
Mandoline: Model Evaluation under Distribution Shift
Mayee F. Chen
Karan Goel
N. Sohoni
Fait Poms
Kayvon Fatahalian
Christopher Ré
28
69
0
01 Jul 2021
Combining Feature and Instance Attribution to Detect Artifacts
Combining Feature and Instance Attribution to Detect Artifacts
Pouya Pezeshkpour
Sarthak Jain
Sameer Singh
Byron C. Wallace
TDI
18
43
0
01 Jul 2021
The MultiBERTs: BERT Reproductions for Robustness Analysis
The MultiBERTs: BERT Reproductions for Robustness Analysis
Thibault Sellam
Steve Yadlowsky
Jason W. Wei
Naomi Saphra
Alexander DÁmour
...
Iulia Turc
Jacob Eisenstein
Dipanjan Das
Ian Tenney
Ellie Pavlick
24
93
0
30 Jun 2021
Knowledge-Grounded Self-Rationalization via Extractive and Natural
  Language Explanations
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations
Bodhisattwa Prasad Majumder
Oana-Maria Camburu
Thomas Lukasiewicz
Julian McAuley
25
35
0
25 Jun 2021
Automatic Construction of Evaluation Suites for Natural Language
  Generation Datasets
Automatic Construction of Evaluation Suites for Natural Language Generation Datasets
Simon Mille
Kaustubh D. Dhole
Saad Mahamood
Laura Perez-Beltrachini
Varun Gangal
Mihir Kale
Emiel van Miltenburg
Sebastian Gehrmann
ELM
42
22
0
16 Jun 2021
Learning Stable Classifiers by Transferring Unstable Features
Learning Stable Classifiers by Transferring Unstable Features
Yujia Bao
Shiyu Chang
Regina Barzilay
OOD
32
8
0
15 Jun 2021
An Empirical Survey of Data Augmentation for Limited Data Learning in
  NLP
An Empirical Survey of Data Augmentation for Limited Data Learning in NLP
Jiaao Chen
Derek Tam
Colin Raffel
Joey Tianyi Zhou
Diyi Yang
28
172
0
14 Jun 2021
Examining and Combating Spurious Features under Distribution Shift
Examining and Combating Spurious Features under Distribution Shift
Chunting Zhou
Xuezhe Ma
Paul Michel
Graham Neubig
OOD
32
66
0
14 Jun 2021
A Little Robustness Goes a Long Way: Leveraging Robust Features for
  Targeted Transfer Attacks
A Little Robustness Goes a Long Way: Leveraging Robust Features for Targeted Transfer Attacks
Jacob Mitchell Springer
Melanie Mitchell
Garrett Kenyon
AAML
31
43
0
03 Jun 2021
SyGNS: A Systematic Generalization Testbed Based on Natural Language
  Semantics
SyGNS: A Systematic Generalization Testbed Based on Natural Language Semantics
Hitomi Yanaka
K. Mineshima
Kentaro Inui
NAI
AI4CE
38
11
0
02 Jun 2021
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers
Yujia Bao
Shiyu Chang
Regina Barzilay
24
20
0
26 May 2021
LMMS Reloaded: Transformer-based Sense Embeddings for Disambiguation and
  Beyond
LMMS Reloaded: Transformer-based Sense Embeddings for Disambiguation and Beyond
Daniel Loureiro
A. Jorge
Jose Camacho-Collados
35
26
0
26 May 2021
Evaluating Gender Bias in Natural Language Inference
Evaluating Gender Bias in Natural Language Inference
Shanya Sharma
Manan Dey
Koustuv Sinha
28
41
0
12 May 2021
Understanding by Understanding Not: Modeling Negation in Language Models
Understanding by Understanding Not: Modeling Negation in Language Models
Arian Hosseini
Siva Reddy
Dzmitry Bahdanau
R. Devon Hjelm
Alessandro Sordoni
Rameswar Panda
22
87
0
07 May 2021
Is Incoherence Surprising? Targeted Evaluation of Coherence Prediction
  from Language Models
Is Incoherence Surprising? Targeted Evaluation of Coherence Prediction from Language Models
Anne Beyer
Sharid Loáiciga
David Schlangen
27
15
0
07 May 2021
Evaluating Attribution in Dialogue Systems: The BEGIN Benchmark
Evaluating Attribution in Dialogue Systems: The BEGIN Benchmark
Nouha Dziri
Hannah Rashkin
Tal Linzen
David Reitter
ALM
195
79
0
30 Apr 2021
Explanation-Based Human Debugging of NLP Models: A Survey
Explanation-Based Human Debugging of NLP Models: A Survey
Piyawat Lertvittayakumjorn
Francesca Toni
LRM
42
79
0
30 Apr 2021
Why AI is Harder Than We Think
Why AI is Harder Than We Think
Melanie Mitchell
36
95
0
26 Apr 2021
Modeling Event Plausibility with Consistent Conceptual Abstraction
Modeling Event Plausibility with Consistent Conceptual Abstraction
Ian Porada
Kaheer Suleman
Adam Trischler
Jackie C.K. Cheung
113
19
0
20 Apr 2021
Improving Question Answering Model Robustness with Synthetic Adversarial
  Data Generation
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation
Max Bartolo
Tristan Thrush
Robin Jia
Sebastian Riedel
Pontus Stenetorp
Douwe Kiela
AAML
28
103
0
18 Apr 2021
Back to Square One: Artifact Detection, Training and Commonsense
  Disentanglement in the Winograd Schema
Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema
Yanai Elazar
Hongming Zhang
Yoav Goldberg
Dan Roth
ReLM
LRM
45
44
0
16 Apr 2021
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