Who cites «Annotation Error Detection: Analyzing the Past and Present for a More Coherent Future»

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

1. Beyond Annotator Disagreement: Guideline-Induced Errors in Arabic Hate Speech Annotation — 2026 · Proceedings of the 20th Linguistic Annotation Workshop (LAW XX)
2. Dataset Cartography for Implicit Discourse Relation Recognition: Promises and Pitfalls — 2026 · Proceedings of the 2nd Joint Workshop on Computational Approaches to Discourse, Context and Document-Level Inferences and Computational Models of Reference, Anaphora and Coreference (CODI-CRAC 2026)
3. Detecting Potentially Under-annotated Explicit Discourse Connectives in the Penn Discourse Treebank (PDTB-3) with LLMs — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
4. EVADE: LLM-Based Explanation Generation and Validation for Error Detection in NLI — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
5. Explainable Semantic Textual Similarity via Dissimilar Span Detection — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
6. Extending Retag to Conversion Error Detection: A Case Study on SynTagRus Morphology — 2026 · Proceedings of the Ninth Workshop on Universal Dependencies (UDW 2026)
7. Gold Label Errors in the SciFact Benchmark: An LLM-Assisted Annotation Audit — 2026 · BioNLP 2026
8. Human Label Variation in Implicit Discourse Relation Recognition — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
9. UD-CHILDES-BG: a dependency treebank of Bulgarian child and child-directed speech — 2026 · Proceedings of the 20th Linguistic Annotation Workshop (LAW XX)
10. Using Model Disagreement to Identify Unstable Regions in MT Evaluation — 2026 · Proceedings of the 26th Annual Conference of the European Association for Machine Translation (Volume 1)
11. When Ground Truth Disagrees: A Human-in-the-Loop Audit of Annotation Errors in High-Stakes Crash Narratives — 2026 · Proceedings of the 20th Linguistic Annotation Workshop (LAW XX)
12. Annotating the Annotators: Analysis, Insights and Modelling from an Annotation Campaign on Persuasion Techniques Detection — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
13. Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
14. Benchmarking the Benchmarks: Reproducing Climate-Related NLP Tasks — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
15. Facts Fade Fast: Evaluating Memorization of Outdated Medical Knowledge in Large Language Models — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
16. Token-Level Metrics for Detecting Incorrect Gold Annotations in Named Entity Recognition — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
17. Analyzing Dataset Annotation Quality Management in the Wild — 2024 · Computational Linguistics
18. Donkii: Characterizing and Detecting Errors in Instruction-Tuning Datasets — 2024 · Proceedings of the 18th Linguistic Annotation Workshop (LAW-XVIII)
19. Interpreting Predictive Probabilities: Model Confidence or Human Label Variation? — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)
20. Large Language Models: A New Approach for Privacy Policy Analysis at Scale — 2024 · arXiv:2405.20900 · Computing, vol. 106, no. 12, pp. 3879-3903, 2024
21. Multi-Label Classification for Implicit Discourse Relation Recognition — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
22. NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
23. On Efficient and Statistical Quality Estimation for Data Annotation — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
24. ToMBench: Benchmarking Theory of Mind in Large Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
25. 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)
26. ActiveAED: A Human in the Loop Improves Annotation Error Detection — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
27. Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
28. Temporal and Second Language Influence on Intra-Annotator Agreement and Stability in Hate Speech Labelling — 2023 · Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)
29. 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)
30. Zero-Shot Data Maps. Efficient Dataset Cartography Without Model Training — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
31. Stop Measuring Calibration When Humans Disagree — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
32. 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