Who cites «Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference» · page 4

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

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model — 2022 · arXiv:2201.11990
VALUE: Understanding Dialect Disparity in NLU — our card · 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
ViNLI: A Vietnamese Corpus for Studies on Open-Domain Natural Language Inference — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation — 2022 · arXiv:2201.05955
When Chosen Wisely, More Data Is What You Need: A Universal Sample-Efficient Strategy For Data Augmentation — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
When Does Syntax Mediate Neural Language Model Performance? Evidence from Dropout Probes — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Why is Winoground Hard? Investigating Failures in Visuolinguistic Compositionality — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Word Order Does Matter and Shuffled Language Models Know It — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Your fairness may vary: Pretrained language model fairness in toxic text classification — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
``No, They Did Not'''': Dialogue Response Dynamics in Pre-trained Language Models — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
``Will You Find These Shortcuts?'''' A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classification — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
e-CARE: a New Dataset for Exploring Explainable Causal Reasoning — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
A Deep Metric Learning Approach to Account Linking — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
A Logic-Based Framework for Natural Language Inference in Dutch — 2021 · arXiv:2110.03323
A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs — 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
AESOP: Paraphrase Generation with Adaptive Syntactic Control — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Abstraction and analogy-making in artificial intelligence — 2021
Alignment Rationale for Natural Language Inference — 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)
An Empirical Comparison of Instance Attribution Methods for NLP — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Annotation Difficulties in Natural Language Inference — 2021 · Proceedings of the 13th Brazilian Symposium in Information and Human Language Technology
Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Are NLP Models really able to Solve Simple Math Word Problems? — our card · 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Are Rotten Apples Edible? Challenging Commonsense Inference Ability with Exceptions — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Assessing the Generalization Capacity of Pre-trained Language Models through Japanese Adversarial Natural Language Inference — 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Benchmarking Machine Reading Comprehension: A Psychological Perspective — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond — 2021 · arXiv:2109.00725
Changing the World by Changing the Data — 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)
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition — 2021 · Transactions of the Association for Computational Linguistics
Contrastive Explanations for Model Interpretability — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction — 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
Debiasing Methods in Natural Language Understanding Make Bias More Accessible — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Does Putting a Linguist in the Loop Improve NLU Data Collection? — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning 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 2: Short Papers)
Don''t Discard All the Biased Instances: Investigating a Core Assumption in Dataset Bias Mitigation Techniques — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
Dynabench: Rethinking Benchmarking in NLP — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
ESC: Redesigning WSD with Extractive Sense Comprehension — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Effective Batching for Recurrent Neural Network Grammars — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
End-to-End Self-Debiasing Framework for Robust NLU Training — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Evaluating Document Coherence Modeling — 2021 · Transactions of the Association for Computational Linguistics
Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP — 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)
Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? — 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)
ExCAR: Event Graph Knowledge Enhanced Explainable Causal Reasoning — 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)
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Explaining Contextualization in Language Models using Visual Analytics — 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)
Explanation-Based Human Debugging of NLP Models: A Survey — 2021 · Transactions of the Association for Computational Linguistics
Exploring Lexical Irregularities in Hypothesis-Only Models of Natural Language Inference — 2021 · arXiv:2101.07397
Exploring Transitivity in Neural NLI Models through Veridicality — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Factual Probing Is [MASK]: Learning vs. Learning to Recall — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Gender Bias in Machine Translation — 2021 · Transactions of the Association for Computational Linguistics
Generalising to German Plural Noun Classes, from the Perspective of a Recurrent Neural Network — 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics — 2021 · Proceedings of the Second Workshop on Insights from Negative Results in NLP
Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
HILDIF: Interactive Debugging of NLI Models Using Influence Functions — 2021 · Proceedings of the First Workshop on Interactive Learning for Natural Language Processing
HateCheck: Functional Tests for Hate Speech Detection 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)
HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalizability — 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)
How Fast can BERT Learn Simple Natural Language Inference? — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Identifying inherent disagreement in natural language inference — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Implicitly Abusive Language – What does it actually look like and why are we not getting there? — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
IndoNLI: A Natural Language Inference Dataset for Indonesian — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Investigating the Effect of Natural Language Explanations on Out-of-Distribution Generalization in Few-shot NLI — 2021 · Proceedings of the Second Workshop on Insights from Negative Results in NLP
Is Incoherence Surprising? Targeted Evaluation of Coherence Prediction from Language Models — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Is Supervised Syntactic Parsing Beneficial for Language Understanding Tasks? An Empirical Investigation — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Issues with Entailment-based Zero-shot Text Classification — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases — 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)
Look at that! BERT can be easily distracted from paying attention to morphosyntax — 2021 · Proceedings of the Society for Computation in Linguistics 2021
MATE-KD: Masked Adversarial TExt, a Companion to Knowledge Distillation — 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)
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Measuring Association Between Labels and Free-Text Rationales — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Measuring and Improving Consistency in Pretrained Language Models — 2021
MedNLI Is Not Immune: Natural Language Inference Artifacts in the Clinical Domain — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)
Modeling Event Plausibility with Consistent Conceptual Abstraction — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Multitask Prompted Training Enables Zero-Shot Task Generalization — 2021 · arXiv:2110.08207
Muppet: Massive Multi-task Representations with Pre-Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
NOPE: A Corpus of Naturally-Occurring Presuppositions in English — our card · 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
NeuralLog: Natural Language Inference with Joint Neural and Logical Reasoning — 2021 · Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics
Numerical reasoning in machine reading comprehension tasks: are we there yet? — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
On the Interaction of Belief Bias and Explanations — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
On the Interplay Between Fine-tuning and Composition in Transformers — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
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)
Posterior Differential Regularization with f-divergence for Improving Model Robustness — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Pragmatic competence of pre-trained language models through the lens of discourse connectives — 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
Probing Language Models for Understanding of Temporal Expressions — 2021 · Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
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
Regressive Ensemble for Machine Translation Quality Evaluation — 2021 · Proceedings of the Sixth Conference on Machine Translation
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
SELFEXPLAIN: A Self-Explaining Architecture for Neural Text Classifiers — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
SICK-NL: A Dataset for Dutch Natural Language Inference — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
SICKNL: A Dataset for Dutch Natural Language Inference — 2021 · arXiv:2101.05716
SPECTRA: Sparse Structured Text Rationalization — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Self-Supervised Test-Time Learning for Reading Comprehension — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Semantic Data Set Construction from Human Clustering and Spatial Arrangement — 2021 · Computational Linguistics
Separating Retention from Extraction in the Evaluation of End-to-end Relation Extraction — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

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