annotator modeling

Examining the Utility of Self-disclosure Types for Modeling Annotators of Social Norms EACL 2026 Reciprocal Teaching: Dynamic Multi-Model Teacher-Student Learning for Multiple Noisy Annotations WACV 2026 Task Assignment meets Annotator Modeling: Human-LLM Collaborative Annotation with Constraints ACL 2026 McMaster at LeWiDi-2025: Demographic-Aware RoBERTa EMNLP 2025 NLP-ResTeam at LeWiDi-2025:Performance Shifts in Perspective Aware Models based on Evaluation Metrics EMNLP 2025 Accurate and Data-Efficient Toxicity Prediction when Annotators Disagree EMNLP 2024 Capturing Perspectives of Crowdsourced Annotators in Subjective Learning Tasks NAACL 2024 Corpus Considerations for Annotator Modeling and Scaling NAACL 2024 Coupled Confusion Correction: Learning from Crowds with Sparse Annotations AAAI 2024 The Whole Is Bigger Than the Sum of Its Parts: Modeling Individual Annotators to Capture Emotional Variability Interspeech 2024 Architectural Sweet Spots for Modeling Human Label Variation by the Example of Argument Quality: It’s Best to Relate Perspectives! EMNLP 2023 SafeWebUH at SemEval-2023 Task 11: Learning Annotator Disagreement in Derogatory Text: Comparison of Direct Training vs Aggregation SemEval 2023 The Ecological Fallacy in Annotation: Modeling Human Label Variation goes beyond Sociodemographics ACL 2023 Identifying Chinese Opinion Expressions with Extremely-Noisy Crowdsourcing Annotations ACL 2022 Unifying Data Perspectivism and Personalization: An Application to Social Norms EMNLP 2022 Learning from Crowds by Modeling Common Confusions AAAI 2021 Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms NeurIPS 2019 An Expectation Maximization Approach to Joint Modeling of Multidimensional Ratings Derived from Multiple Annotators Interspeech 2016 Crowdclustering NeurIPS 2011 The Multidimensional Wisdom of Crowds NeurIPS 2010