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

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

Pages: 1 · 2 · 3

  1. Measuring and Mitigating Shortcut Reliance in Language Models with Probe-Based Representation Entanglement — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
  2. NormWorlds-CF: Solver-Verified Counterfactual Normative Reasoning with Metamorphic-Relation GRPO — 2026 · arXiv:2607.03957
  3. Parallel Universes, Parallel Languages: A Comprehensive Study on LLM-based Multilingual Counterfactual Example Generation — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  4. An Investigation of Robustness of LLMs in Mathematical Reasoning: Benchmarking with Mathematically-Equivalent Transformation of Advanced Mathematical Problems — 2025 · arXiv:2508.08833
  5. Evaluation of Attribution Bias in Generator-Aware Retrieval-Augmented Large Language Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  6. Found in Translation: Measuring Multilingual LLM Consistency as Simple as Translate then Evaluate — 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
  7. LinguaLens: Towards Interpreting Linguistic Mechanisms of Large Language Models via Sparse Auto-Encoder — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  8. MRAG: A Modular Retrieval Framework for Time-Sensitive Question Answering — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  9. NeoQA: Evidence-based Question Answering with Generated News Events — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  10. On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  11. People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  12. Revisiting Implicitly Abusive Language Detection: Evaluating LLMs in Zero-Shot and Few-Shot Settings — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  13. SCORE: Systematic COnsistency and Robustness Evaluation for Large Language Models — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 3: Industry Track)
  14. Truth or Twist? Optimal Model Selection for Reliable Label Flipping Evaluation in LLM-based Counterfactuals — 2025 · Proceedings of the 18th International Natural Language Generation Conference
  15. Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  16. reWordBench: Benchmarking and Improving the Robustness of Reward Models with Transformed Inputs — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  17. A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  18. A Survey on Natural Language Counterfactual Generation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  19. AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  20. Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  21. Beyond Agreement: Diagnosing the Rationale Alignment of Automated Essay Scoring Methods based on Linguistically-informed Counterfactuals — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  22. CEval: A Benchmark for Evaluating Counterfactual Text Generation — 2024 · Proceedings of the 17th International Natural Language Generation Conference
  23. Chaining Event Spans for Temporal Relation Grounding — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  24. Cutting Through the Noise: Boosting LLM Performance on Math Word Problems — our card · 2024 · arXiv:2406.15444
  25. Desiderata For The Context Use Of Question Answering Systems — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  26. Efficient Lifelong Model Evaluation in an Era of Rapid Progress — 2024 · arXiv:2402.19472
  27. Evaluating ChatGPT against Functionality Tests for Hate Speech Detection — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  28. GuardBench: A Large-Scale Benchmark for Guardrail Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  29. How Often Are Errors in Natural Language Reasoning Due to Paraphrastic Variability? — 2024 · Transactions of the Association for Computational Linguistics
  30. Improving Adversarial Data Collection by Supporting Annotators: Lessons from GAHD, a German Hate Speech Dataset — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  31. LJPCheck: Functional Tests for Legal Judgment Prediction — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  32. LLMs for Generating and Evaluating Counterfactuals: A Comprehensive Study — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  33. Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  34. NevIR: Negation in Neural Information Retrieval — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  35. One Thousand and One Pairs: A ``novel'''' challenge for long-context language models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  36. PairCFR: Enhancing Model Training on Paired Counterfactually Augmented Data through Contrastive Learning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  37. Principles from Clinical Research for NLP Model Generalization — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  38. RORA: Robust Free-Text Rationale Evaluation — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  39. Seemingly Plausible Distractors in Multi-Hop Reasoning: Are Large Language Models Attentive Readers? — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  40. SynthEval: Hybrid Behavioral Testing of NLP Models with Synthetic CheckLists — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  41. The Art of Saying No: Contextual Noncompliance in Language Models — 2024 · arXiv:2407.12043
  42. Unsupervised Contrast-Consistent Ranking with Language Models — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  43. V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimization — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  44. Whispers of Doubt Amidst Echoes of Triumph in NLP Robustness — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  45. A Multilingual Evaluation of NER Robustness to Adversarial Inputs — 2023 · Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP 2023)
  46. A Pretrainer''s Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity — 2023 · arXiv:2305.13169
  47. An Overview Of Temporal Commonsense Reasoning and Acquisition — 2023 · arXiv:2308.00002
  48. Benchmarking Long-tail Generalization with Likelihood Splits — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
  49. COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  50. COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  51. CREST: A Joint Framework for Rationalization and Counterfactual Text Generation — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  52. Can NLI Provide Proper Indirect Supervision for Low-resource Biomedical Relation Extraction? — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  53. Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  54. Cold-Start Data Selection for Better Few-shot Language Model Fine-tuning: A Prompt-based Uncertainty Propagation Approach — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  55. Counterfactual Active Learning for Out-of-Distribution Generalization — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  56. DISCO: Distilling Counterfactuals with Large Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  57. Data Curation Alone Can Stabilize In-context Learning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  58. Deductive Additivity for Planning of Natural Language Proofs — 2023 · Proceedings of the 1st Workshop on Natural Language Reasoning and Structured Explanations (NLRSE)
  59. DistillCSE: Distilled Contrastive Learning for Sentence Embeddings — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  60. Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses? — our card · 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  61. EXPLAIN, EDIT, GENERATE: Rationale-Sensitive Counterfactual Data Augmentation for Multi-hop Fact Verification — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  62. Euphemistic Abuse – A New Dataset and Classification Experiments for Implicitly Abusive Language — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  63. Evaluating the Rationale Understanding of Critical Reasoning in Logical Reading Comprehension — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  64. Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions — 2023 · Transactions of the Association for Computational Linguistics
  65. Fighting Bias With Bias: Promoting Model Robustness by Amplifying Dataset Biases — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  66. GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-Distribution Generalization Perspective — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  67. Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  68. NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation — 2023 · Northern European Journal of Language Technology
  69. NormBank: A Knowledge Bank of Situational Social Norms — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  70. Out-of-Distribution Generalization in Natural Language Processing: Past, Present, and Future — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  71. People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  72. ReCode: Robustness Evaluation of Code Generation Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  73. Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks — 2023 · arXiv:2307.02477
  74. Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity — 2023 · arXiv:2301.12867
  75. SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  76. ScoNe: Benchmarking Negation Reasoning in Language Models With Fine-Tuning and In-Context Learning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  77. SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models — 2023 · arXiv:2311.08370
  78. Sociodemographic Bias in Language Models: A Survey and Forward Path — 2023 · arXiv:2306.08158
  79. Stubborn Lexical Bias in Data and Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  80. The Trickle-down Impact of Reward (In-)consistency on RLHF — 2023 · arXiv:2309.16155
  81. XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models — 2023 · arXiv:2308.01263
  82. (Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models'' Performance — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  83. ANLIzing the Adversarial Natural Language Inference Dataset — 2022 · Proceedings of the Society for Computation in Linguistics 2022
  84. Adaptive Testing and Debugging of NLP Models — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  85. Analyzing Dynamic Adversarial Training Data in the Limit — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  86. AutoCAD: Automatically Generate Counterfactuals for Mitigating Shortcut Learning — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  87. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models — 2022 · arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj
  88. CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  89. CORE: A Retrieve-then-Edit Framework for Counterfactual Data Generation — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  90. Can Transformers Reason in Fragments of Natural Language? — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  91. Cascading Biases: Investigating the Effect of Heuristic Annotation Strategies on Data and Models — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  92. Challenges in Applying Explainability Methods to Improve the Fairness of NLP Models — 2022 · Proceedings of the 2nd Workshop on Trustworthy Natural Language Processing (TrustNLP 2022)
  93. CommonsenseQA 2.0: Exposing the Limits of AI through Gamification — 2022 · arXiv:2201.05320
  94. Consistency Training with Virtual Adversarial Discrete Perturbation — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  95. Contrast Sets for Stativity of English Verbs in Context — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  96. Contrastive Data and Learning for Natural Language Processing — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts
  97. Corpus-Guided Contrast Sets for Morphosyntactic Feature Detection in Low-Resource English Varieties — 2022 · Proceedings of the First Workshop on NLP applications to field linguistics
  98. Counterfactually Augmented Data and Unintended Bias: The Case of Sexism and Hate Speech Detection — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  99. De-Bias for Generative Extraction in Unified NER Task — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  100. Deep Learning for Text Style Transfer: A Survey — 2022 · Computational Linguistics

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