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HELP: A Dataset for Identifying Shortcomings of Neural Models in
  Monotonicity Reasoning

HELP: A Dataset for Identifying Shortcomings of Neural Models in Monotonicity Reasoning

International Workshop on Semantic Evaluation (SemEval), 2019
27 April 2019
Hitomi Yanaka
K. Mineshima
D. Bekki
Kentaro Inui
Satoshi Sekine
Lasha Abzianidze
Johan Bos
ArXiv (abs)PDFHTML

Papers citing "HELP: A Dataset for Identifying Shortcomings of Neural Models in Monotonicity Reasoning"

45 / 45 papers shown
Title
How to Improve the Robustness of Closed-Source Models on NLI
How to Improve the Robustness of Closed-Source Models on NLI
Joe Stacey
Lisa Alazraki
Aran Ubhi
Beyza Ermis
Aaron Mueller
Marek Rei
244
0
0
26 May 2025
How Hard is this Test Set? NLI Characterization by Exploiting Training
  Dynamics
How Hard is this Test Set? NLI Characterization by Exploiting Training DynamicsConference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Adrian Cosma
Stefan Ruseti
Mihai Dascalu
Cornelia Caragea
115
4
0
04 Oct 2024
Self-Evolving GPT: A Lifelong Autonomous Experiential Learner
Self-Evolving GPT: A Lifelong Autonomous Experiential Learner
Jinglong Gao
Xiao Ding
Yiming Cui
Jianbai Zhao
Hepeng Wang
Ting Liu
Bing Qin
KELMCLL
188
11
0
12 Jul 2024
Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning
  through Logical Fallacy Understanding
Reason from Fallacy: Enhancing Large Language Models' Logical Reasoning through Logical Fallacy Understanding
Yanda Li
Dixuan Wang
Jiaqing Liang
Guochao Jiang
Qi He
Yanghua Xiao
Deqing Yang
LRMELM
163
15
0
04 Apr 2024
Estimating the Causal Effects of Natural Logic Features in
  Transformer-Based NLI Models
Estimating the Causal Effects of Natural Logic Features in Transformer-Based NLI ModelsInternational Conference on Language Resources and Evaluation (LREC), 2024
Julia Rozanova
Marco Valentino
André Freitas
CML
155
1
0
03 Apr 2024
Task-Oriented Paraphrase Analytics
Task-Oriented Paraphrase Analytics
Marcel Gohsen
Matthias Hagen
Martin Potthast
Benno Stein
195
1
0
26 Mar 2024
GLoRE: Evaluating Logical Reasoning of Large Language Models
GLoRE: Evaluating Logical Reasoning of Large Language Models
Hanmeng Liu
Zhiyang Teng
Ruoxi Ning
Jian Liu
Qiji Zhou
Yuexin Zhang
Yue Zhang
ReLMELMLRM
310
8
0
13 Oct 2023
Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference
Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference
Sushma A. Akoju
Robert Vacareanu
Haris Riaz
Eduardo Blanco
Mihai Surdeanu
CoGeNAI
147
1
0
11 Jul 2023
NatLogAttack: A Framework for Attacking Natural Language Inference
  Models with Natural Logic
NatLogAttack: A Framework for Attacking Natural Language Inference Models with Natural LogicAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Zióu Zheng
Xiao-Dan Zhu
AAMLLRM
214
6
0
06 Jul 2023
SpaceNLI: Evaluating the Consistency of Predicting Inferences in Space
SpaceNLI: Evaluating the Consistency of Predicting Inferences in Space
Lasha Abzianidze
J. Zwarts
Yoad Winter
93
4
0
05 Jul 2023
Evaluating Paraphrastic Robustness in Textual Entailment Models
Evaluating Paraphrastic Robustness in Textual Entailment ModelsAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Dhruv Verma
Yash Kumar Lal
Shreyashee Sinha
Benjamin Van Durme
Adam Poliak
240
7
0
29 Jun 2023
ScoNe: Benchmarking Negation Reasoning in Language Models With
  Fine-Tuning and In-Context Learning
ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context LearningAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
Jingyuan Selena She
Christopher Potts
Sam Bowman
Atticus Geiger
208
22
0
30 May 2023
Simple Linguistic Inferences of Large Language Models (LLMs): Blind
  Spots and Blinds
Simple Linguistic Inferences of Large Language Models (LLMs): Blind Spots and Blinds
Victoria Basmov
Yoav Goldberg
Reut Tsarfaty
ReLMLRM
192
8
0
24 May 2023
Estimating the Causal Effects of Natural Logic Features in Neural NLI
  Models
Estimating the Causal Effects of Natural Logic Features in Neural NLI Models
Julia Rozanova
Marco Valentino
André Freitas
CML
126
4
0
15 May 2023
Interventional Probing in High Dimensions: An NLI Case Study
Interventional Probing in High Dimensions: An NLI Case StudyFindings (Findings), 2023
Julia Rozanova
Marco Valentino
Lucas C. Cordeiro
André Freitas
83
8
0
20 Apr 2023
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4
Hanmeng Liu
Ruoxi Ning
Zhiyang Teng
Jian Liu
Qiji Zhou
Yuexin Zhang
ELMReLMLRM
324
304
0
07 Apr 2023
Natural Language Reasoning, A Survey
Natural Language Reasoning, A SurveyACM Computing Surveys (ACM Comput. Surv.), 2023
Fei Yu
Hongbo Zhang
Prayag Tiwari
Benyou Wang
ReLMLRM
270
94
0
26 Mar 2023
tasksource: A Dataset Harmonization Framework for Streamlined NLP
  Multi-Task Learning and Evaluation
tasksource: A Dataset Harmonization Framework for Streamlined NLP Multi-Task Learning and Evaluation
Damien Sileo
166
13
0
14 Jan 2023
TestAug: A Framework for Augmenting Capability-based NLP Tests
TestAug: A Framework for Augmenting Capability-based NLP TestsInternational Conference on Computational Linguistics (COLING), 2022
Guanqun Yang
Mirazul Haque
Qiaochu Song
Wei Yang
Xueqing Liu
ELM
136
0
0
14 Oct 2022
FOLIO: Natural Language Reasoning with First-Order Logic
FOLIO: Natural Language Reasoning with First-Order LogicConference on Empirical Methods in Natural Language Processing (EMNLP), 2022
Simeng Han
Hailey Schoelkopf
Yilun Zhao
Zhenting Qi
Martin Riddell
...
Yingbo Zhou
Caiming Xiong
Rex Ying
Arman Cohan
Dragomir R. Radev
ReLMLRM
309
149
0
02 Sep 2022
Penguins Don't Fly: Reasoning about Generics through Instantiations and
  Exceptions
Penguins Don't Fly: Reasoning about Generics through Instantiations and ExceptionsConference of the European Chapter of the Association for Computational Linguistics (EACL), 2022
Emily Allaway
Jena D. Hwang
Chandra Bhagavatula
Kathleen McKeown
Doug Downey
Yejin Choi
LRM
136
23
0
23 May 2022
Systematicity, Compositionality and Transitivity of Deep NLP Models: a
  Metamorphic Testing Perspective
Systematicity, Compositionality and Transitivity of Deep NLP Models: a Metamorphic Testing PerspectiveFindings (Findings), 2022
Edoardo Manino
Julia Rozanova
Danilo S. Carvalho
André Freitas
Lucas C. Cordeiro
157
10
0
26 Apr 2022
Curriculum: A Broad-Coverage Benchmark for Linguistic Phenomena in
  Natural Language Understanding
Curriculum: A Broad-Coverage Benchmark for Linguistic Phenomena in Natural Language UnderstandingNorth American Chapter of the Association for Computational Linguistics (NAACL), 2022
Zeming Chen
Qiyue Gao
ELM
193
4
0
13 Apr 2022
An Analysis of Negation in Natural Language Understanding Corpora
An Analysis of Negation in Natural Language Understanding CorporaAnnual Meeting of the Association for Computational Linguistics (ACL), 2022
Md Mosharaf Hossain
Dhivya Chinnappa
Eduardo Blanco
183
48
0
16 Mar 2022
Neuro-symbolic Natural Logic with Introspective Revision for Natural
  Language Inference
Neuro-symbolic Natural Logic with Introspective Revision for Natural Language InferenceTransactions of the Association for Computational Linguistics (TACL), 2022
Yufei Feng
Xiaoyu Yang
Xiao-Dan Zhu
Michael A. Greenspan
LRMNAI
338
13
0
09 Mar 2022
Decomposing Natural Logic Inferences in Neural NLI
Decomposing Natural Logic Inferences in Neural NLI
Julia Rozanova
Deborah Ferreira
Marco Valentino
Mokanrarangan Thayaparan
André Freitas
NAILRM
170
5
0
15 Dec 2021
A Logic-Based Framework for Natural Language Inference in Dutch
A Logic-Based Framework for Natural Language Inference in Dutch
Lasha Abzianidze
Konstantinos Kogkalidis
209
4
0
07 Oct 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
LRMNAI
149
14
0
18 Sep 2021
Transformers in the loop: Polarity in neural models of language
Transformers in the loop: Polarity in neural models of languageAnnual Meeting of the Association for Computational Linguistics (ACL), 2021
Lisa Bylinina
Alexey Tikhonov
113
0
0
08 Sep 2021
Investigating Transfer Learning in Multilingual Pre-trained Language
  Models through Chinese Natural Language Inference
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language InferenceFindings (Findings), 2021
Hai Hu
He Zhou
Zuoyu Tian
Yiwen Zhang
Yina Ma
Yanting Li
Yixin Nie
Kyle Richardson
151
12
0
07 Jun 2021
NeuralLog: Natural Language Inference with Joint Neural and Logical
  Reasoning
NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning
Zeming Chen
Qiyue Gao
Lawrence S. Moss
FedMLNAI
213
47
0
29 May 2021
Supporting Context Monotonicity Abstractions in Neural NLI Models
Supporting Context Monotonicity Abstractions in Neural NLI Models
Julia Rozanova
Deborah Ferreira
Mokanarangan Thayaparan
Marco Valentino
André Freitas
84
10
0
17 May 2021
Does Putting a Linguist in the Loop Improve NLU Data Collection?
Does Putting a Linguist in the Loop Improve NLU Data Collection?Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021
Alicia Parrish
William Huang
Omar Agha
Soo-hwan Lee
Nikita Nangia
Alex Warstadt
Karmanya Aggarwal
Emily Allaway
Tal Linzen
Samuel R. Bowman
180
48
0
15 Apr 2021
Exploring Transitivity in Neural NLI Models through Veridicality
Exploring Transitivity in Neural NLI Models through VeridicalityConference of the European Chapter of the Association for Computational Linguistics (EACL), 2021
Hitomi Yanaka
K. Mineshima
Kentaro Inui
165
23
0
26 Jan 2021
Attentive Tree-structured Network for Monotonicity Reasoning
Attentive Tree-structured Network for Monotonicity Reasoning
Zeming Chen
LRM
66
2
0
03 Jan 2021
Exploring End-to-End Differentiable Natural Logic Modeling
Exploring End-to-End Differentiable Natural Logic Modeling
Yufei Feng
Zióu Zheng
Quan Liu
Michael A. Greenspan
Xiao-Dan Zhu
161
15
0
08 Nov 2020
ANLIzing the Adversarial Natural Language Inference Dataset
ANLIzing the Adversarial Natural Language Inference Dataset
Adina Williams
Tristan Thrush
Douwe Kiela
AAML
363
48
0
24 Oct 2020
Beyond Leaderboards: A survey of methods for revealing weaknesses in
  Natural Language Inference data and models
Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models
Viktor Schlegel
Goran Nenadic
Riza Batista-Navarro
ELM
171
18
0
29 May 2020
Do Neural Models Learn Systematicity of Monotonicity Inference in
  Natural Language?
Do Neural Models Learn Systematicity of Monotonicity Inference in Natural Language?Annual Meeting of the Association for Computational Linguistics (ACL), 2020
Hitomi Yanaka
K. Mineshima
D. Bekki
Kentaro Inui
NAI
145
52
0
30 Apr 2020
Neural Natural Language Inference Models Partially Embed Theories of
  Lexical Entailment and Negation
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation
Atticus Geiger
Kyle Richardson
Christopher Potts
219
4
0
30 Apr 2020
Syntactic Data Augmentation Increases Robustness to Inference Heuristics
Syntactic Data Augmentation Increases Robustness to Inference HeuristicsAnnual Meeting of the Association for Computational Linguistics (ACL), 2020
Junghyun Min
R. Thomas McCoy
Dipanjan Das
Emily Pitler
Tal Linzen
216
189
0
24 Apr 2020
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature
  and PRESupposition
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESuppositionAnnual Meeting of the Association for Computational Linguistics (ACL), 2020
Paloma Jeretic
Alex Warstadt
Suvrat Bhooshan
Adina Williams
ReLMAI4CE
305
126
0
07 Apr 2020
Posing Fair Generalization Tasks for Natural Language Inference
Posing Fair Generalization Tasks for Natural Language InferenceConference on Empirical Methods in Natural Language Processing (EMNLP), 2019
Atticus Geiger
Ignacio Cases
L. Karttunen
Christopher Potts
180
49
0
03 Nov 2019
Probing Natural Language Inference Models through Semantic Fragments
Probing Natural Language Inference Models through Semantic FragmentsAAAI Conference on Artificial Intelligence (AAAI), 2019
Kyle Richardson
Hai Hu
L. Moss
Ashish Sabharwal
209
150
0
16 Sep 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
202
86
0
15 Jun 2019
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