Who cites «Breaking NLI Systems with Sentences that Require Simple Lexical Inferences» · page 2

202 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning — 2021 · Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics
NoiseQA: Challenge Set Evaluation for User-Centric Question Answering — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Probing Pre-Trained Language Models for Disease Knowledge — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Robustness Gym: Unifying the NLP Evaluation Landscape — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations
Robustness and Sensitivity of BERT Models Predicting Alzheimer's Disease from Text — 2021 · Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)
SyGNS: A Systematic Generalization Testbed Based on Natural Language Semantics — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
TabPert : An Effective Platform for Tabular Perturbation — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Understanding Model Robustness to User-generated Noisy Texts — 2021 · Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)
A guide to the dataset explosion in QA, NLI, and commonsense reasoning — our card · 2020 · Proceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts
Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
Adversarial NLI: A New Benchmark for Natural Language Understanding — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
An Analysis of Natural Language Inference Benchmarks through the Lens of Negation — our card · 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language Inference — 2020 · Proceedings of the 24th Conference on Computational Natural Language Learning
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models — 2020
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition — our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
BERT-ATTACK: Adversarial Attack Against BERT Using BERT — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models — 2020 · arXiv:2005.14709
ConjNLI: Natural Language Inference Over Conjunctive Sentences — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
ContraCAT: Contrastive Coreference Analytical Templates for Machine Translation — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Decomposing and Comparing Meaning Relations: Paraphrasing, Textual Entailment, Contradiction, and Specificity — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Discriminatively-Tuned Generative Classifiers for Robust Natural Language Inference — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Do Neural Models Learn Systematicity of Monotonicity Inference in Natural Language? — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Evaluating Models' Local Decision Boundaries via Contrast Sets — our card · 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
Evaluation of Coreference Resolution Systems Under Adversarial Attacks — 2020 · Proceedings of the First Workshop on Computational Approaches to Discourse
Experience Grounds Language — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
GenAug: Data Augmentation for Finetuning Text Generators — 2020 · Proceedings of Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning Architectures
How does Punctuation Affect Neural Models in Natural Language Inference — 2020 · Proceedings of the Probability and Meaning Conference (PaM 2020)
Hy-NLI: a Hybrid system for Natural Language Inference — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
INFOTABS: Inference on Tables as Semi-structured Data — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Iterative Feature Mining for Constraint-Based Data Collection to Increase Data Diversity and Model Robustness — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Knowledge-Enhanced Natural Language Inference Based on Knowledge Graphs — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
Language (Re)modelling: Towards Embodied Language Understanding — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Learning as Abduction: Trainable Natural Logic Theorem Prover for Natural Language Inference — 2020 · Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics
Mining Knowledge for Natural Language Inference from Wikipedia Categories — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
More Bang for Your Buck: Natural Perturbation for Robust Question Answering — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and Negation — our card · 2020 · Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT — 2020 · Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics
Robustness to Modification with Shared Words in Paraphrase Identification — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
Shortcut Learning in Deep Neural Networks — 2020 · arXiv:2004.07780
Stance Detection Benchmark: How Robust Is Your Stance Detection? — 2020 · arXiv:2001.01565
Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
The Extraordinary Failure of Complement Coercion Crowdsourcing — 2020 · Proceedings of the First Workshop on Insights from Negative Results in NLP
Towards Debiasing NLU Models from Unknown Biases — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Towards Robustifying NLI Models Against Lexical Dataset Biases — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Translation Artifacts in Cross-lingual Transfer Learning — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
What Does My QA Model Know? Devising Controlled Probes Using Expert Knowledge — 2020 · Transactions of the Association for Computational Linguistics
Word-level Textual Adversarial Attacking as Combinatorial Optimization — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
A Logic-Driven Framework for Consistency of Neural Models — 2019 · arXiv:1909.00126
A logical-based corpus for cross-lingual evaluation — 2019 · Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)
Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Adversarial Analysis of Natural Language Inference Systems — 2019 · arXiv:1912.03441
Analysis Methods in Neural Language Processing: A Survey — 2019 · Transactions of the Association for Computational Linguistics
Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Can Neural Networks Understand Monotonicity Reasoning? — 2019 · Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP
Combating Adversarial Misspellings with Robust Word Recognition — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Composition of Sentence Embeddings: Lessons from Statistical Relational Learning — 2019 · Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
Deep Learning for Natural Language Inference — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorials
Deep Neural Model Inspection and Comparison via Functional Neuron Pathways — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Diversify Your Datasets: Analyzing Generalization via Controlled Variance in Adversarial Datasets — 2019 · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
Do Nuclear Submarines Have Nuclear Captains? A Challenge Dataset for Commonsense Reasoning over Adjectives and Objects — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Don''t Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Don''t Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
EQUATE: A Benchmark Evaluation Framework for Quantitative Reasoning in Natural Language Inference — our card · 2019 · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
Explaining Simple Natural Language Inference — 2019 · Proceedings of the 13th Linguistic Annotation Workshop
HELP: A Dataset for Identifying Shortcomings of Neural Models in Monotonicity Reasoning — 2019 · Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
HellaSwag: Can a Machine Really Finish Your Sentence? — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Learning the Difference that Makes a Difference with Counterfactually-Augmented Data — 2019 · arXiv:1909.12434
Mining Discourse Markers for Unsupervised Sentence Representation Learning — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Misleading Failures of Partial-input Baselines — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Multi-Task Deep Neural Networks for Natural Language Understanding — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Neural Text Summarization: A Critical Evaluation — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification — 2019 · arXiv:1908.11828
PAWS: Paraphrase Adversaries from Word Scrambling — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Posing Fair Generalization Tasks for Natural Language Inference — 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Probing Natural Language Inference Models through Semantic Fragments — 2019 · arXiv:1909.07521
Probing Neural Network Comprehension of Natural Language Arguments — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches — 2019 · arXiv:1904.01172
SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference — our card · 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Shifting the Baseline: Single Modality Performance on Visual Navigation & QA — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Understanding Roles and Entities: Datasets and Models for Natural Language Inference — 2019 · arXiv:1904.09720
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual — 2019 · Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)
pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples — 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Analyzing Compositionality-Sensitivity of NLI Models — 2018 · arXiv:1811.07033
Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Frame- and Entity-Based Knowledge for Common-Sense Argumentative Reasoning — 2018 · Proceedings of the 5th Workshop on Argument Mining
How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks — our card · 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Improving Large-Scale Fact-Checking using Decomposable Attention Models and Lexical Tagging — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
Stress-Testing Neural Models of Natural Language Inference with Multiply-Quantified Sentences — 2018 · arXiv:1810.13033