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

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  1. Leveraging Annotator Disagreement for Text Classification — 2024 · Proceedings of the 7th International Conference on Natural Language and Speech Processing (ICNLSP 2024)
  2. MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  3. Multi-Task Learning with Adapters for Plausibility Prediction: Bridging the Gap or Falling into the Trenches? — 2024 · Proceedings of the Fifth Workshop on Insights from Negative Results in NLP
  4. SIGA: A Naturalistic NLI Dataset of English Scalar Implicatures with Gradable Adjectives — our card · 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  5. Scalable and Domain-General Abstractive Proposition Segmentation — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  6. Sentence-Space Metrics (SSM) for the Evaluation of Sentence Comprehension — 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)
  7. SenticVec: Toward Robust and Human-Centric Neurosymbolic Sentiment Analysis — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  8. The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct Representation — 2024 · arXiv:2405.01299 · https://aclanthology.org/2024.nlperspectives-1.11/
  9. The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  10. The Unreasonable Effectiveness of Easy Training Data for Hard Tasks — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  11. Through the Lens of Split Vote: Exploring Disagreement, Difficulty and Calibration in Legal Case Outcome Classification — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  12. VariErr NLI: Separating Annotation Error from Human Label Variation — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  13. What''s Mine becomes Yours: Defining, Annotating and Detecting Context-Dependent Paraphrases in News Interview Dialogs — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  14. X-PARADE: Cross-Lingual Textual Entailment and Information Divergence across Paragraphs — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  15. ``Seeing the Big through the Small'''': Can LLMs Approximate Human Judgment Distributions on NLI from a Few Explanations? — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  16. ``Tell me who you are and I tell you how you argue'''': Predicting Stances and Arguments for Stakeholder Groups — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  17. ALANNO: An Active Learning Annotation System for Mortals — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
  18. Analyzing Cognitive Plausibility of Subword Tokenization — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  19. Annotation Error Detection: Analyzing the Past and Present for a More Coherent Future — our card · 2023 · Computational Linguistics
  20. Are Language Models Worse than Humans at Following Prompts? It's Complicated — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  21. COMPS: Conceptual Minimal Pair Sentences for testing Robust Property Knowledge and its Inheritance in Pre-trained Language Models — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  22. Can Large Language Models Capture Dissenting Human Voices? — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  23. Clarify When Necessary: Resolving Ambiguity Through Interaction with LMs — 2023 · arXiv:2311.09469
  24. Collective Human Opinions in Semantic Textual Similarity — 2023 · Transactions of the Association for Computational Linguistics
  25. Common Law Annotations: Investigating the Stability of Dialog System Output Annotations — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  26. Conflicts, Villains, Resolutions: Towards models of Narrative Media Framing — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  27. Crowdsourcing Veridicality Annotations in Spanish: Can Speakers Actually Agree? — 2023 · Proceedings of the 8th Student Research Workshop associated with the International Conference Recent Advances in Natural Language Processing
  28. Culturally Aware Natural Language Inference — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  29. Curing the SICK and Other NLI Maladies — 2023 · Computational Linguistics
  30. DISCO: Distilling Counterfactuals with Large Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  31. Data Factors for Better Compositional Generalization — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  32. Deep Model Compression Also Helps Models Capture Ambiguity — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  33. Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design — 2023
  34. Disagreement Matters: Preserving Label Diversity by Jointly Modeling Item and Annotator Label Distributions with DisCo — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  35. Ecologically Valid Explanations for Label Variation in NLI — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  36. Expectations over Unspoken Alternatives Predict Pragmatic Inferences — our card · 2023
  37. Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  38. FairPrism: Evaluating Fairness-Related Harms in Text Generation — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  39. From Dissonance to Insights: Dissecting Disagreements in Rationale Construction for Case Outcome Classification — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  40. Hate Speech Classifiers Learn Normative Social Stereotypes — 2023 · Transactions of the Association for Computational Linguistics
  41. It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  42. LEDA: a Large-Organization Email-Based Decision-Dialogue-Act Analysis Dataset — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  43. No Strong Feelings One Way or Another: Re-operationalizing Neutrality in Natural Language Inference — 2023 · Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)
  44. On Degrees of Freedom in Defining and Testing Natural Language Understanding — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  45. PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
  46. Quirk or Palmer: A Comparative Study of Modal Verb Frameworks with Annotated Datasets — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
  47. SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created through Human-Machine Collaboration — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  48. SafeWebUH at SemEval-2023 Task 11: Learning Annotator Disagreement in Derogatory Text: Comparison of Direct Training vs Aggregation — 2023 · Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
  49. SemEval-2023 Task 11: Learning with Disagreements (LeWiDi) — 2023 · Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
  50. Sources of Noise in Dialogue and How to Deal with Them — 2023 · Proceedings of the 24th Annual Meeting of the Special Interest Group on Discourse and Dialogue
  51. The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generation — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  52. Uncertainty-Aware Natural Language Inference with Stochastic Weight Averaging — 2023 · Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
  53. Understanding and Predicting Human Label Variation in Natural Language Inference through Explanation — 2023 · arXiv:2304.12443
  54. Unveiling the Multi-Annotation Process: Examining the Influence of Annotation Quantity and Instance Difficulty on Model Performance — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  55. VECHR: A Dataset for Explainable and Robust Classification of Vulnerability Type in the European Court of Human Rights — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  56. Vicarious Offense and Noise Audit of Offensive Speech Classifiers: Unifying Human and Machine Disagreement on What is Offensive — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  57. We're Afraid Language Models Aren't Modeling Ambiguity — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  58. What is the Real Intention behind this Question? Dataset Collection and Intention Classification — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  59. What's the Meaning of Superhuman Performance in Today's NLU? — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  60. When Do Annotator Demographics Matter? Measuring the Influence of Annotator Demographics with the POPQUORN Dataset — 2023 · Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)
  61. When Truth Matters - Addressing Pragmatic Categories in Natural Language Inference (NLI) by Large Language Models (LLMs) — 2023 · Proceedings of the 12th Joint Conference on Lexical and Computational Semantics (*SEM 2023)
  62. When the Majority is Wrong: Modeling Annotator Disagreement for Subjective Tasks — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  63. Which Examples Should be Multiply Annotated? Active Learning When Annotators May Disagree — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  64. Whose Opinions Do Language Models Reflect? — 2023 · arXiv:2303.17548
  65. Why Did the Chicken Cross the Road? Rephrasing and Analyzing Ambiguous Questions in VQA — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  66. You Are What You Annotate: Towards Better Models through Annotator Representations — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  67. Zero and Few-shot Semantic Parsing with Ambiguous Inputs — 2023 · arXiv:2306.00824
  68. ALLSH: Active Learning Guided by Local Sensitivity and Hardness — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  69. ANLIzing the Adversarial Natural Language Inference Dataset — 2022 · Proceedings of the Society for Computation in Linguistics 2022
  70. Analyzing Dynamic Adversarial Training Data in the Limit — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  71. Analyzing the Effects of Annotator Gender across NLP Tasks — 2022 · Proceedings of the 1st Workshop on Perspectivist Approaches to NLP @LREC2022
  72. Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  73. ArMIS - The Arabic Misogyny and Sexism Corpus with Annotator Subjective Disagreements — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  74. Capture Human Disagreement Distributions by Calibrated Networks for Natural Language Inference — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  75. Challenges and Strategies in Cross-Cultural NLP — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  76. Clean or Annotate: How to Spend a Limited Data Collection Budget — 2022 · Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing
  77. CoRAL: a Context-aware Croatian Abusive Language Dataset — 2022 · Findings of the Association for Computational Linguistics: AACL-IJCNLP 2022
  78. ComFact: A Benchmark for Linking Contextual Commonsense Knowledge — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  79. Compositional Evaluation on Japanese Textual Entailment and Similarity — 2022 · Transactions of the Association for Computational Linguistics
  80. Critical Perspectives: A Benchmark Revealing Pitfalls in PerspectiveAPI — 2022 · Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)
  81. Disentangling Uncertainty in Machine Translation Evaluation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  82. Distributed NLI: Learning to Predict Human Opinion Distributions for Language Reasoning — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  83. Investigating Reasons for Disagreement in Natural Language Inference — 2022 · Transactions of the Association for Computational Linguistics
  84. Natural Language Deduction through Search over Statement Compositions — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  85. Noisy Label Regularisation for Textual Regression — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  86. Norm Participation Grounds Language — 2022 · Proceedings of the 2022 CLASP Conference on (Dis)embodiment
  87. Overconfidence in the Face of Ambiguity with Adversarial Data — 2022 · Proceedings of the First Workshop on Dynamic Adversarial Data Collection
  88. Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  89. Stop Measuring Calibration When Humans Disagree — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  90. Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  91. 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)
  92. The ``Problem'''' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  93. Two Contrasting Data Annotation Paradigms for Subjective NLP Tasks — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  94. Uncovering Surprising Event Boundaries in Narratives — 2022 · Proceedings of the 4th Workshop of Narrative Understanding (WNU2022)
  95. WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation — 2022 · arXiv:2201.05955
  96. (Mis)alignment Between Stance Expressed in Social Media Data and Public Opinion Surveys — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  97. Agree to Disagree: Analysis of Inter-Annotator Disagreements in Human Evaluation of Machine Translation Output — 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
  98. Analyzing Stereotypes in Generative Text Inference Tasks — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  99. Annotation Difficulties in Natural Language Inference — 2021 · Proceedings of the 13th Brazilian Symposium in Information and Human Language Technology
  100. Beyond Black & White: Leveraging Annotator Disagreement via Soft-Label Multi-Task Learning — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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