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Who cites «Adversarial Examples for Evaluating Reading Comprehension Systems»

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

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  1. Beyond Static Synthetic Noise: Assessing the Robustness of Large Language Models to Natural Context Variation in the Real World — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  2. DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution — 2026 · Findings of the Association for Computational Linguistics: EACL 2026
  3. Do Images Speak Louder than Words? Investigating the Effect of Textual Misinformation in VLMs — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  4. FLUKE: A Linguistically-Driven and Task-Agnostic Framework for Robustness Evaluation — 2026 · Findings of the Association for Computational Linguistics: EACL 2026
  5. GSM-Noise: Exploring and Enhancing Large Language Models'' Reasoning under Noisy Inputs — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  6. Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  7. Moneyball with LLMs: Analyzing Tabular Summarization in Sports Narratives — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  8. MultiWikiQA: A Reading Comprehension Benchmark in 300+ Languages — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
  9. Parameter-Efficient Quantum NLP for Paraphrase Detection: Performance, Robustness, and Entanglement — 2026 · arXiv:2609.14529
  10. StanceAttack: Adversarial Attack for Stance Detection — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  11. TruthTrap: A Bilingual Benchmark for Evaluating Factually Correct Yet Misleading Information in Question Answering — 2026 · Findings of the Association for Computational Linguistics: EACL 2026
  12. Uncovering Currency Bias and Syntax Gap in Text Embedding Models — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  13. Cancer-Myth: Evaluating Large Language Models on Patient Questions with False Presuppositions — 2025 · arXiv:2504.11373
  14. Corpus Poisoning via Approximate Greedy Gradient Descent — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  15. Is your benchmark truly adversarial? AdvScore: Evaluating Human-Grounded Adversarialness — 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)
  16. Machine Translation Meta Evaluation through Translation Accuracy Challenge Sets — 2025 · Computational Linguistics
  17. Normative Conflicts and Shallow AI Alignment — 2025 · arXiv:2506.04679 · Milliere, R. (2025). Normative conflicts and shallow AI alignment. Philosophical Studies, 1-44
  18. YESciEval: Robust LLM-as-a-Judge for Scientific Question Answering — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  19. A Comprehensive Survey of Contamination Detection Methods in Large Language Models — 2024 · arXiv:2404.00699
  20. Adversarial Math Word Problem Generation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  21. 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)
  22. CATfOOD: Counterfactual Augmented Training for Improving Out-of-Domain Performance and Calibration — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  23. Characterizing LLM Abstention Behavior in Science QA with Context Perturbations — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  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. Do LLMs Overcome Shortcut Learning? An Evaluation of Shortcut Challenges in Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  27. ECON: On the Detection and Resolution of Evidence Conflicts — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  28. Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  29. EvoGrad: A Dynamic Take on the Winograd Schema Challenge with Human Adversaries — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  30. Explore Spurious Correlations at the Concept Level in Language Models for Text Classification — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  31. Fast Adversarial Attacks on Language Models In One GPU Minute — 2024 · arXiv:2402.15570
  32. Finding a Needle in the Adversarial Haystack: A Targeted Paraphrasing Approach For Uncovering Edge Cases with Minimal Distribution Distortion — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  33. Instructing Large Language Models to Identify and Ignore Irrelevant Conditions — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  34. Machine Translation Testing via Syntactic Tree Pruning — 2024 · arXiv:2401.00751
  35. Mass-Editing Memory with Attention in Transformers: A cross-lingual exploration of knowledge — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  36. Navigating the Shortcut Maze: A Comprehensive Analysis of Shortcut Learning in Text Classification by Language Models — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  37. Predicting Machine Translation Performance on Low-Resource Languages: The Role of Domain Similarity — 2024 · Findings of the Association for Computational Linguistics: EACL 2024
  38. RE-RAG: Improving Open-Domain QA Performance and Interpretability with Relevance Estimator in Retrieval-Augmented Generation — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  39. Random Smooth-based Certified Defense against Text Adversarial Attack — 2024 · Findings of the Association for Computational Linguistics: EACL 2024
  40. ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  41. Robust and Scalable Model Editing for Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  42. The Art of Saying No: Contextual Noncompliance in Language Models — 2024 · arXiv:2407.12043
  43. The Llama 3 Herd of Models — 2024 · arXiv:2407.21783
  44. Think Twice: Measuring the Efficiency of Eliminating Prediction Shortcuts of Question Answering Models — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  45. Two Heads are Better than One: Nested PoE for Robust Defense Against Multi-Backdoors — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  46. VISREAS: Complex Visual Reasoning with Unanswerable Questions — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  47. What Evidence Do Language Models Find Convincing? — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  48. 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)
  49. ``Knowing When You Don''t Know'''': A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented Generation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  50. A Lightweight Method to Generate Unanswerable Questions in English — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  51. A Multilingual Evaluation of NER Robustness to Adversarial Inputs — 2023 · Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP 2023)
  52. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation — 2023 · arXiv:2305.11391
  53. Adversarial Text Generation by Search and Learning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  54. An Empirical Survey of Data Augmentation for Limited Data Learning in NLP — 2023 · Transactions of the Association for Computational Linguistics
  55. Are aligned neural networks adversarially aligned? — 2023 · arXiv:2306.15447
  56. Assessing Out-of-Domain Language Model Performance from Few Examples — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  57. Automatically Auditing Large Language Models via Discrete Optimization — 2023 · arXiv:2303.04381
  58. BITE: Textual Backdoor Attacks with Iterative Trigger Injection — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  59. CCL23-Eval 任务9总结报告:汉语高考阅读理解对抗鲁棒评测 (Overview of CCL23-Eval Task 9: Adversarial Robustness Evaluation for Chinese Gaokao Reading Comprehension) — 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
  60. Causal Intervention for Mitigating Name Bias in Machine Reading Comprehension — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  61. Certified Robustness to Text Adversarial Attacks by Randomized [MASK] — 2023 · Computational Linguistics
  62. DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models — 2023 · arXiv:2306.11698
  63. Did the Models Understand Documents? Benchmarking Models for Language Understanding in Document-Level Relation Extraction — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  64. Do Question Answering Modeling Improvements Hold Across Benchmarks? — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  65. Document-Level Event Argument Extraction With a Chain Reasoning Paradigm — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  66. Don''t Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  67. Fighting Bias With Bias: Promoting Model Robustness by Amplifying Dataset Biases — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  68. Guiding LLM to Fool Itself: Automatically Manipulating Machine Reading Comprehension Shortcut Triggers — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  69. HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark — our card · 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  70. How Fragile is Relation Extraction under Entity Replacements? — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
  71. INVITE: a Testbed of Automatically Generated Invalid Questions to Evaluate Large Language Models for Hallucinations — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  72. Improving Zero-shot Reader by Reducing Distractions from Irrelevant Documents in Open-Domain Question Answering — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  73. Improving the robustness of NLI models with minimax training — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  74. Inferring Capabilities from Task Performance with Bayesian Triangulation — 2023 · arXiv:2309.11975
  75. Jamp: Controlled Japanese Temporal Inference Dataset for Evaluating Generalization Capacity of Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
  76. Large Language Models Can Be Easily Distracted by Irrelevant Context — 2023 · arXiv:2302.00093
  77. Large Language Models Can be Lazy Learners: Analyze Shortcuts in In-Context Learning — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  78. Learning the Legibility of Visual Text Perturbations — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  79. Low-Resource Languages Jailbreak GPT-4 — 2023 · arXiv:2310.02446
  80. Making Retrieval-Augmented Language Models Robust to Irrelevant Context — 2023 · arXiv:2310.01558
  81. MeetingQA: Extractive Question-Answering on Meeting Transcripts — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  82. Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
  83. Mitigating Biases in Hate Speech Detection from A Causal Perspective — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  84. Model-tuning Via Prompts Makes NLP Models Adversarially Robust — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  85. NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation — 2023 · Northern European Journal of Language Technology
  86. Noisy Exemplars Make Large Language Models More Robust: A Domain-Agnostic Behavioral Analysis — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  87. Post-Abstention: Towards Reliably Re-Attempting the Abstained Instances in QA — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  88. RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answering — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  89. Robust Natural Language Understanding with Residual Attention Debiasing — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  90. RobustGEC: Robust Grammatical Error Correction Against Subtle Context Perturbation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  91. Similarizing the Influence of Words with Contrastive Learning to Defend Word-level Adversarial Text Attack — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  92. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks — 2023 · arXiv:2310.10844
  93. The Earth is Flat because...: Investigating LLMs'' Belief towards Misinformation via Persuasive Conversation — 2023 · arXiv:2312.09085
  94. The Trickle-down Impact of Reward (In-)consistency on RLHF — 2023 · arXiv:2309.16155
  95. Towards Building a Robust Toxicity Predictor — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track)
  96. Translated Benchmarks Can Be Misleading: the Case of Estonian Question Answering — 2023 · Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
  97. Universal and Transferable Adversarial Attacks on Aligned Language Models — 2023 · arXiv:2307.15043
  98. Using contradictions improves question answering systems — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  99. When and Why Does Bias Mitigation Work? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  100. Which Spurious Correlations Impact Reasoning in NLI Models? A Visual Interactive Diagnosis through Data-Constrained Counterfactuals — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)

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