ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1902.01007
  4. Cited By
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 / 293 papers shown
Title
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 Chen
Hua-Hong Wu
Haifeng Wang
17
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
457
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
334
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
13
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
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
39
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
24
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
29
66
0
14 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
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
33
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
20
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
Aaron C. Courville
11
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
19
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
192
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
17
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
39
44
0
16 Apr 2021
Supervising Model Attention with Human Explanations for Robust Natural
  Language Inference
Supervising Model Attention with Human Explanations for Robust Natural Language Inference
Joe Stacey
Yonatan Belinkov
Marek Rei
30
45
0
16 Apr 2021
Masked Language Modeling and the Distributional Hypothesis: Order Word
  Matters Pre-training for Little
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little
Koustuv Sinha
Robin Jia
Dieuwke Hupkes
J. Pineau
Adina Williams
Douwe Kiela
45
243
0
14 Apr 2021
Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in
  Visual Question Answering
Beyond Question-Based Biases: Assessing Multimodal Shortcut Learning in Visual Question Answering
Corentin Dancette
Rémi Cadène
Damien Teney
Matthieu Cord
CML
28
75
0
07 Apr 2021
What Will it Take to Fix Benchmarking in Natural Language Understanding?
What Will it Take to Fix Benchmarking in Natural Language Understanding?
Samuel R. Bowman
George E. Dahl
ELM
ALM
30
156
0
05 Apr 2021
Thinking Aloud: Dynamic Context Generation Improves Zero-Shot Reasoning
  Performance of GPT-2
Thinking Aloud: Dynamic Context Generation Improves Zero-Shot Reasoning Performance of GPT-2
Gregor Betz
Kyle Richardson
Christian Voigt
ReLM
LRM
16
29
0
24 Mar 2021
Automatic Generation of Contrast Sets from Scene Graphs: Probing the
  Compositional Consistency of GQA
Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA
Yonatan Bitton
Gabriel Stanovsky
Roy Schwartz
Michael Elhadad
CoGe
22
33
0
17 Mar 2021
Are NLP Models really able to Solve Simple Math Word Problems?
Are NLP Models really able to Solve Simple Math Word Problems?
Arkil Patel
S. Bhattamishra
Navin Goyal
ReLM
LRM
27
764
0
12 Mar 2021
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU
  Models
Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU Models
Mengnan Du
Varun Manjunatha
R. Jain
Ruchi Deshpande
Franck Dernoncourt
Jiuxiang Gu
Tong Sun
Xia Hu
57
105
0
11 Mar 2021
Contrastive Explanations for Model Interpretability
Contrastive Explanations for Model Interpretability
Alon Jacovi
Swabha Swayamdipta
Shauli Ravfogel
Yanai Elazar
Yejin Choi
Yoav Goldberg
44
95
0
02 Mar 2021
Measuring and Improving Consistency in Pretrained Language Models
Measuring and Improving Consistency in Pretrained Language Models
Yanai Elazar
Nora Kassner
Shauli Ravfogel
Abhilasha Ravichander
Eduard H. Hovy
Hinrich Schütze
Yoav Goldberg
HILM
263
346
0
01 Feb 2021
Muppet: Massive Multi-task Representations with Pre-Finetuning
Muppet: Massive Multi-task Representations with Pre-Finetuning
Armen Aghajanyan
Anchit Gupta
Akshat Shrivastava
Xilun Chen
Luke Zettlemoyer
Sonal Gupta
24
266
0
26 Jan 2021
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and
  Improving Models
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models
Tongshuang Wu
Marco Tulio Ribeiro
Jeffrey Heer
Daniel S. Weld
41
240
0
01 Jan 2021
How Do Your Biomedical Named Entity Recognition Models Generalize to
  Novel Entities?
How Do Your Biomedical Named Entity Recognition Models Generalize to Novel Entities?
Hyunjae Kim
Jaewoo Kang
AI4CE
84
21
0
01 Jan 2021
FastIF: Scalable Influence Functions for Efficient Model Interpretation
  and Debugging
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging
Han Guo
Nazneen Rajani
Peter Hase
Joey Tianyi Zhou
Caiming Xiong
TDI
41
102
0
31 Dec 2020
HateCheck: Functional Tests for Hate Speech Detection Models
HateCheck: Functional Tests for Hate Speech Detection Models
Paul Röttger
B. Vidgen
Dong Nguyen
Zeerak Talat
Helen Z. Margetts
J. Pierrehumbert
31
259
0
31 Dec 2020
Infusing Finetuning with Semantic Dependencies
Infusing Finetuning with Semantic Dependencies
Zhaofeng Wu
Hao Peng
Noah A. Smith
22
36
0
10 Dec 2020
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural
  Networks
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks
L. N. Darlow
Stanisław Jastrzębski
Amos Storkey
48
24
0
19 Nov 2020
Gradient Starvation: A Learning Proclivity in Neural Networks
Gradient Starvation: A Learning Proclivity in Neural Networks
Mohammad Pezeshki
Sekouba Kaba
Yoshua Bengio
Aaron Courville
Doina Precup
Guillaume Lajoie
MLT
50
257
0
18 Nov 2020
Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles
Learning to Model and Ignore Dataset Bias with Mixed Capacity Ensembles
Christopher Clark
Mark Yatskar
Luke Zettlemoyer
18
61
0
07 Nov 2020
Underspecification Presents Challenges for Credibility in Modern Machine
  Learning
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander DÁmour
Katherine A. Heller
D. Moldovan
Ben Adlam
B. Alipanahi
...
Kellie Webster
Steve Yadlowsky
T. Yun
Xiaohua Zhai
D. Sculley
OffRL
53
669
0
06 Nov 2020
Previous
123456
Next