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home / docs / papers / cited-by / Who cites «Evaluating Models' Local Decision Boundaries via Contrast Sets» · page 2

Who cites «Evaluating Models' Local Decision Boundaries via Contrast Sets» · page 2

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

Pages: 1 · 2 · 3

  1. ER-Test: Evaluating Explanation Regularization Methods for Language Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  2. Exploring The Landscape of Distributional Robustness for Question Answering Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  3. Exposing the Limits of Video-Text Models through Contrast Sets — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  4. FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. HateCheckHIn: Evaluating Hindi Hate Speech Detection Models — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  6. Hatemoji: A Test Suite and Adversarially-Generated Dataset for Benchmarking and Detecting Emoji-Based Hate — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  7. Holistic Evaluation of Language Models — 2022 · arXiv:2211.09110 · Published in Transactions on Machine Learning Research (TMLR), 2023
  8. Identifying Implicitly Abusive Remarks about Identity Groups using a Linguistically Informed Approach — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  9. InferES : A Natural Language Inference Corpus for Spanish Featuring Negation-Based Contrastive and Adversarial Examples — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  10. Investigating the Performance of Transformer-Based NLI Models on Presuppositional Inferences — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  11. Lexical Generalization Improves with Larger Models and Longer Training — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  12. Machine Reading, Fast and Slow: When Do Models ``Understand'''' Language? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  13. 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
  14. 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
  15. Multilingual HateCheck: Functional Tests for Multilingual Hate Speech Detection Models — 2022 · Proceedings of the Sixth Workshop on Online Abuse and Harms (WOAH)
  16. Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  17. Prompting GPT-3 To Be Reliable — 2022 · arXiv:2210.09150
  18. ROSE: Robust Selective Fine-tuning for Pre-trained Language Models — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  19. Retrieval-guided Counterfactual Generation for QA — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  20. 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
  21. RobustLR: A Diagnostic Benchmark for Evaluating Logical Robustness of Deductive Reasoners — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  22. Semantically Distributed Robust Optimization for Vision-and-Language Inference — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  23. State-of-the-art generalisation research in NLP: A taxonomy and review — 2022 · arXiv:2210.03050 · Nat Mach Intell 5, 1161-1174 (2023)
  24. Tailor: Generating and Perturbing Text with Semantic Controls — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  25. 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
  26. 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)
  27. Towards a Unified Multi-Dimensional Evaluator for Text Generation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  28. 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)
  29. 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)
  30. What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  31. 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
  32. A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs — 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
  33. Active Learning by Acquiring Contrastive Examples — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  34. Are Factuality Checkers Reliable? Adversarial Meta-evaluation of Factuality in Summarization — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  35. 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
  36. Are Rotten Apples Edible? Challenging Commonsense Inference Ability with Exceptions — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  37. Automatic Generation of Contrast Sets from Scene Graphs: Probing the Compositional Consistency of GQA — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  38. 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
  39. 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
  40. Better Robustness by More Coverage: Adversarial and Mixup Data Augmentation for Robust Finetuning — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  41. CLINE: Contrastive Learning with Semantic Negative Examples for Natural Language Understanding — 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)
  42. COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  43. Can NLI Models Verify QA Systems' Predictions? — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  44. CausaLM: Causal Model Explanation Through Counterfactual Language Models — 2021 · Computational Linguistics
  45. Causal Augmentation for Causal Sentence Classification — 2021 · Proceedings of the First Workshop on Causal Inference and NLP
  46. Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond — 2021 · arXiv:2109.00725
  47. Competency Problems: On Finding and Removing Artifacts in Language Data — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  48. Connecting Attributions and QA Model Behavior on Realistic Counterfactuals — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  49. Contrastive Explanations for Model Interpretability — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  50. 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)
  51. CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  52. Detecting over/under-translation errors for determining adequacy in human translations — 2021 · arXiv:2104.00267
  53. Does Putting a Linguist in the Loop Improve NLU Data Collection? — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  54. 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
  55. Entity-Based Knowledge Conflicts in Question Answering — 2021 · arXiv:2109.05052
  56. Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  57. 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)
  58. Evaluation Paradigms in Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  59. Explaining NLP Models via Minimal Contrastive Editing (MiCE) — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  60. Extracting Temporal Event Relation with Syntax-guided Graph Transformer — 2021 · arXiv:2104.09570
  61. Generalization in Instruction Following Systems — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  62. 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
  63. 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)
  64. 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)
  65. How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs? — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  66. I Wish I Would Have Loved This One, But I Didn't – A Multilingual Dataset for Counterfactual Detection in Product Review — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  67. I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling — 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)
  68. 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
  69. Improving Faithfulness in Abstractive Summarization with Contrast Candidate Generation and Selection — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  70. Joint Universal Syntactic and Semantic Parsing — 2021
  71. Learning to Recognize Dialect Features — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  72. Learning with Instance Bundles for Reading Comprehension — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  73. Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs — 2021 · Transactions of the Association for Computational Linguistics
  74. NOPE: A Corpus of Naturally-Occurring Presuppositions in English — our card · 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
  75. Numerical reasoning in machine reading comprehension tasks: are we there yet? — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  76. Paired Examples as Indirect Supervision in Latent Decision Models — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  77. 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)
  78. Prompting Contrastive Explanations for Commonsense Reasoning Tasks — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  79. Reliability Testing for Natural Language Processing Systems — 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)
  80. SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning — our card · 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  81. Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluation — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  82. TAPAS at SemEval-2021 Task 9: Reasoning over tables with intermediate pre-training — 2021 · Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
  83. Temporal Reasoning on Implicit Events from Distant Supervision — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  84. Tribrid: Stance Classification with Neural Inconsistency Detection — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  85. What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks? — 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)
  86. Wino-X: Multilingual Winograd Schemas for Commonsense Reasoning and Coreference Resolution — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  87. (Re)construing Meaning in NLP — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  88. A Linguistic Analysis of Visually Grounded Dialogues Based on Spatial Expressions — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  89. Aligning AI With Shared Human Values — 2020 · arXiv:2008.02275
  90. Can Humor Prediction Datasets be used for Humor Generation? Humorous Headline Generation via Style Transfer — 2020 · Proceedings of the Second Workshop on Figurative Language Processing
  91. Data and its (dis)contents: A survey of dataset development and use in machine learning research — 2020 · arXiv:2012.05345 · Patterns, Volume 2, Issue 11, 100336. 2021
  92. Experience Grounds Language — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  93. Exposing Shallow Heuristics of Relation Extraction Models with Challenge Data — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  94. Improving Compositional Generalization in Semantic Parsing — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  95. Interpreting Predictions of NLP Models — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts
  96. Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  97. Language (Re)modelling: Towards Embodied Language Understanding — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  98. Learning from Task Descriptions — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  99. Linguistically-Informed Transformations (LIT): A Method for Automatically Generating Contrast Sets — 2020 · Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP
  100. MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

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