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

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  1. A Multilingual Evaluation of NER Robustness to Adversarial Inputs — 2023 · Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP 2023)
  2. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation — 2023 · arXiv:2305.11391
  3. Adversarial Text Generation by Search and Learning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  4. An Empirical Survey of Data Augmentation for Limited Data Learning in NLP — 2023 · Transactions of the Association for Computational Linguistics
  5. Analyzing Pre-trained and Fine-tuned Language Models — 2023 · Proceedings of the Big Picture Workshop
  6. Are aligned neural networks adversarially aligned? — 2023 · arXiv:2306.15447
  7. 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
  8. Automatically Auditing Large Language Models via Discrete Optimization — 2023 · arXiv:2303.04381
  9. 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)
  10. 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)
  11. Causal Intervention for Mitigating Name Bias in Machine Reading Comprehension — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  12. Certified Robustness to Text Adversarial Attacks by Randomized [MASK] — 2023 · Computational Linguistics
  13. Compressing and Debiasing Vision-Language Pre-Trained Models for Visual Question Answering — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  14. Context Quality Matters in Training Fusion-in-Decoder for Extractive Open-Domain Question Answering — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  15. DeSIQ: Towards an Unbiased, Challenging Benchmark for Social Intelligence Understanding — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  16. DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models — 2023 · arXiv:2306.11698
  17. 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)
  18. 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)
  19. 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)
  20. 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)
  21. Empirical Investigation of Neural Symbolic Reasoning Strategies — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
  22. Enhancing Unsupervised Semantic Parsing with Distributed Contextual Representations — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  23. Evaluating and Enhancing the Robustness of Code Pre-trained Models through Structure-Aware Adversarial Samples Generation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  24. Explaining Math Word Problem Solvers — 2023 · arXiv:2307.13128 · Published in 6th International Conference on Natural Language Processing and Information Retrieval (NLPIR 2022)
  25. Exploring Automatically Perturbed Natural Language Explanations in Relation Extraction — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  26. Exploring Schema Generalizability of Text-to-SQL — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  27. FiRo: Finite-context Indexing of Restricted Output Space for NLP Models Facing Noisy Input — 2023 · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  28. Fighting Bias With Bias: Promoting Model Robustness by Amplifying Dataset Biases — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  29. Guiding LLM to Fool Itself: Automatically Manipulating Machine Reading Comprehension Shortcut Triggers — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  30. HeQ: a Large and Diverse Hebrew Reading Comprehension Benchmark — our card · 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  31. How Fragile is Relation Extraction under Entity Replacements? — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
  32. 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
  33. Implications of Annotation Artifacts in Edge Probing Test Datasets — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
  34. 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
  35. 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)
  36. Inferring Capabilities from Task Performance with Bayesian Triangulation — 2023 · arXiv:2309.11975
  37. 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)
  38. Large Language Models Can Be Easily Distracted by Irrelevant Context — 2023 · arXiv:2302.00093
  39. Large Language Models Can be Lazy Learners: Analyze Shortcuts in In-Context Learning — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  40. Learning the Legibility of Visual Text Perturbations — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  41. Learning to Ignore Adversarial Attacks — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  42. Logic Unveils Truth, While Disguise Obscures It: Transition Logic Augmented Response Selection for Multi-Turn Dialogue — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  43. Low-Resource Languages Jailbreak GPT-4 — 2023 · arXiv:2310.02446
  44. Making Retrieval-Augmented Language Models Robust to Irrelevant Context — 2023 · arXiv:2310.01558
  45. Measuring Consistency in Text-based Financial Forecasting Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  46. MeetingQA: Extractive Question-Answering on Meeting Transcripts — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  47. 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)
  48. Mitigating Biases in Hate Speech Detection from A Causal Perspective — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  49. Model-tuning Via Prompts Makes NLP Models Adversarially Robust — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  50. NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation — 2023 · Northern European Journal of Language Technology
  51. NatLogAttack: A Framework for Attacking Natural Language Inference Models with Natural Logic — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  52. No offence, Bert - I insult only humans! Multilingual sentence-level attack on toxicity detection networks — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  53. 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
  54. On Degrees of Freedom in Defining and Testing Natural Language Understanding — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  55. Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script — 2023 · Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023)
  56. PerturbScore: Connecting Discrete and Continuous Perturbations in NLP — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  57. 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)
  58. PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  59. Pseudointelligence: A Unifying Lens on Language Model Evaluation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  60. RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answering — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  61. Robust Natural Language Understanding with Residual Attention Debiasing — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  62. RobustGEC: Robust Grammatical Error Correction Against Subtle Context Perturbation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  63. RobustQA: A Framework for Adversarial Text Generation Analysis on Question Answering Systems — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
  64. 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
  65. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks — 2023 · arXiv:2310.10844
  66. System Report for CCL23-Eval Task 9: HUST1037 Explore Proper Prompt Strategy for LLM in MRC Task — 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
  67. TextVerifier: Robustness Verification for Textual Classifiers with Certifiable Guarantees — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  68. The Earth is Flat because...: Investigating LLMs'' Belief towards Misinformation via Persuasive Conversation — 2023 · arXiv:2312.09085
  69. The Impacts of Unanswerable Questions on the Robustness of Machine Reading Comprehension Models — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  70. The Trickle-down Impact of Reward (In-)consistency on RLHF — 2023 · arXiv:2309.16155
  71. Towards Building a Robust Toxicity Predictor — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track)
  72. Training NLI Models Through Universal Adversarial Attack — 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics
  73. Transformers and the Representation of Biomedical Background Knowledge — 2023 · Computational Linguistics
  74. Translated Benchmarks Can Be Misleading: the Case of Estonian Question Answering — 2023 · Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
  75. Universal and Transferable Adversarial Attacks on Aligned Language Models — 2023 · arXiv:2307.15043
  76. Using contradictions improves question answering systems — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  77. When and Why Does Bias Mitigation Work? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  78. 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)
  79. XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations)
  80. ``World Knowledge'''' in Multiple Choice Reading Comprehension — 2023 · Proceedings of the Sixth Fact Extraction and VERification Workshop (FEVER)
  81. 基于推理链的多跳问答对抗攻击和对抗增强训练方法(Reasoning Chain Based Adversarial Attack and Adversarial Augmentation Training for Multi-hop Question Answering) — 2023 · Proceedings of the 22nd Chinese National Conference on Computational Linguistics
  82. A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  83. A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock Prediction — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  84. ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics — our card · 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)
  85. ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  86. ANLIzing the Adversarial Natural Language Inference Dataset — 2022 · Proceedings of the Society for Computation in Linguistics 2022
  87. ASQA: Factoid Questions Meet Long-Form Answers — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  88. Benchmarking the Covariate Shift Robustness of Open-world Intent Classification Approaches — 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 (Volume 2: Short Papers)
  89. Can Edge Probing Tests Reveal Linguistic Knowledge in QA Models? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  90. Can Explanations Be Useful for Calibrating Black Box Models? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  91. Can Rationalization Improve Robustness? — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  92. Challenges in Generalization in Open Domain Question Answering — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  93. Claim Extraction and Law Matching for COVID-19-related Legislation — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  94. CommonsenseQA 2.0: Exposing the Limits of AI through Gamification — 2022 · arXiv:2201.05320
  95. 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
  96. Data-Efficient Concept Extraction from Pre-trained Language Models for Commonsense Explanation Generation — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  97. Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation — 2022 · Transactions of the Association for Computational Linguistics
  98. DataLab: A Platform for Data Analysis and Intervention — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
  99. Debiasing Masks: A New Framework for Shortcut Mitigation in NLU — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  100. Deep Learning for Text Style Transfer: A Survey — 2022 · Computational Linguistics

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