Who cites «Adversarial Examples for Evaluating Reading Comprehension Systems» · page 3

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

Detecting Textual Adversarial Examples Based on Distributional Characteristics of Data Representations — 2022 · Proceedings of the 7th Workshop on Representation Learning for NLP
Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
DuQM: A Chinese Dataset of Linguistically Perturbed Natural Questions for Evaluating the Robustness of Question Matching Models — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Explaining Dialogue Evaluation Metrics using Adversarial Behavioral Analysis — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Exploring The Landscape of Distributional Robustness for Question Answering Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
FRSUM: Towards Faithful Abstractive Summarization via Enhancing Factual Robustness — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Feeding What You Need by Understanding What You Learned — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Holistic Evaluation of Language Models — 2022 · arXiv:2211.09110 · Published in Transactions on Machine Learning Research (TMLR), 2023
Identifying Human Strategies for Generating Word-Level Adversarial Examples — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Improving the Adversarial Robustness of NLP Models by Information Bottleneck — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Is Neuro-Symbolic AI Meeting its Promise in Natural Language Processing? A Structured Review — 2022 · arXiv:2202.12205 · Semantic Web, vol. Pre-press, no. Pre-press, pp. 1-42, 2022
Learning Invariant Representation Improves Robustness for MRC Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Leveraging Expert Guided Adversarial Augmentation For Improving Generalization in Named Entity Recognition — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Lexical Generalization Improves with Larger Models and Longer Training — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Logical Inference for Counting on Semi-structured Tables — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
Look to the Right: Mitigating Relative Position Bias in Extractive Question Answering — 2022 · Proceedings of the Fifth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
Machine Reading, Fast and Slow: When Do Models ``Understand'''' Language? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Measure and Improve Robustness in NLP Models: A Survey — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Mitigating Dataset Artifacts in Natural Language Inference Through Automatic Contextual Data Augmentation and Learning Optimization — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
NaturalAdversaries: Can Naturalistic Adversaries Be as Effective as Artificial Adversaries? — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
On Length Divergence Bias in Textual Matching Models — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
On the Robustness of Cognate Generation Models — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
On the Robustness of Reading Comprehension Models to Entity Renaming — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
PARSE: An Efficient Search Method for Black-box Adversarial Text Attacks — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Partial-input baselines show that NLI models can ignore context, but they don't. — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Phrase-level Textual Adversarial Attack with Label Preservation — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
PlugAT: A Plug and Play Module to Defend against Textual Adversarial Attack — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Precisely the Point: Adversarial Augmentations for Faithful and Informative Text Generation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Prompting GPT-3 To Be Reliable — 2022 · arXiv:2210.09150
ProoFVer: Natural Logic Theorem Proving for Fact Verification — 2022 · Transactions of the Association for Computational Linguistics
Quantifying Adaptability in Pre-trained Language Models with 500 Tasks — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Rare but Severe Neural Machine Translation Errors Induced by Minimal Deletion: An Empirical Study on Chinese and English — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned — 2022 · arXiv:2209.07858
Red Teaming Language Models with Language Models — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Residue-Based Natural Language Adversarial Attack Detection — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Retrieval-guided Counterfactual Generation for QA — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Robust Question Answering against Distribution Shifts with Test-Time Adaption: An Empirical Study — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
Robust Speech Recognition via Large-Scale Weak Supervision — 2022 · arXiv:2212.04356
SHARP: Search-Based Adversarial Attack for Structured Prediction — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
Self-Supervised Contrastive Learning with Adversarial Perturbations for Defending Word Substitution-based Attacks — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
SemAttack: Natural Textual Attacks via Different Semantic Spaces — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
Semantically Distributed Robust Optimization for Vision-and-Language Inference — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Spa: On the Sparsity of Virtual Adversarial Training for Dependency Parsing — 2022 · Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022
State-of-the-art generalisation research in NLP: A taxonomy and review — 2022 · arXiv:2210.03050 · Nat Mach Intell 5, 1161-1174 (2023)
TAPE: Assessing Few-shot Russian Language Understanding — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
TASA: Deceiving Question Answering Models by Twin Answer Sentences Attack — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Text Characterization Toolkit (TCT) — 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: System Demonstrations
The Dangers of Underclaiming: Reasons for Caution When Reporting How NLP Systems Fail — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
To Answer or Not To Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
TopiOCQA: Open-domain Conversational Question Answering with Topic Switching — 2022 · Transactions of the Association for Computational Linguistics
Towards Adversarially Robust Text Classifiers by Learning to Reweight Clean Examples — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbation — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Training Dynamics for Curriculum Learning: A Study on Monolingual and Cross-lingual NLU — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Unsupervised Domain Adaptation on Question-Answering System with Conversation Data — 2022 · Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue
VALSE: A Task-Independent Benchmark for Vision and Language Models Centered on Linguistic Phenomena — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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)
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation — 2022 · arXiv:2201.05955
Why Should Adversarial Perturbations be Imperceptible? Rethink the Research Paradigm in Adversarial NLP — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
\textitGeneralized but not Robust? Comparing the Effects of Data Modification Methods on Out-of-Domain Generalization and Adversarial Robustness — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Adv-OLM: Generating Textual Adversaries via OLM — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Adversarial Attack against Cross-lingual Knowledge Graph Alignment — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models — 2021 · arXiv:2111.02840
Adversarial Self-Supervised Learning for Out-of-Domain Detection — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Are Factuality Checkers Reliable? Adversarial Meta-evaluation of Factuality in Summarization — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
Are Rotten Apples Edible? Challenging Commonsense Inference Ability with Exceptions — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Attacks against Ranking Algorithms with Text Embeddings: A Case Study on Recruitment Algorithms — 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
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
Benchmarking Robustness of Machine Reading Comprehension Models — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Beyond Accuracy: A Consolidated Tool for Visual Question Answering Benchmarking — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Beyond Laurel/Yanny: An Autoencoder-Enabled Search for Polyperceivable Audio — 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)
COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Can NLI Models Verify QA Systems' Predictions? — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
Can Question Generation Debias Question Answering Models? A Case Study on Question–Context Lexical Overlap — 2021 · Proceedings of the 3rd Workshop on Machine Reading for Question Answering
Can We Improve Model Robustness through Secondary Attribute Counterfactuals? — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
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)
Competency Problems: On Finding and Removing Artifacts in Language Data — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Concealed Data Poisoning Attacks on NLP Models — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Connecting Attributions and QA Model Behavior on Realistic Counterfactuals — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Contextualized Perturbation for Textual Adversarial Attack — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Contribution d'informations syntaxiques aux capacités de généralisation compositionelle des modèles seq2seq convolutifs (Assessing the Contribution of Syntactic Information for Compositional Generalization of seq2seq Convolutional Networks) — 2021 · Actes de la 28e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale
Coreference Reasoning in Machine Reading Comprehension — 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)
Crafting Adversarial Examples for Neural Machine Translation — 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)
Defense against Synonym Substitution-based Adversarial Attacks via Dirichlet Neighborhood Ensemble — 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)
Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 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
DynaSent: A Dynamic Benchmark for Sentiment Analysis — 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)
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
Dynamically Disentangling Social Bias from Task-Oriented Representations with Adversarial Attack — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies