--- title: "Who cites Inherent Disagreements in Human Textual Inferences" description: "240 papers of the Elamur Research library cite «Inherent Disagreements in Human Textual Inferences», found in their bibliographies · page 1 of 2; the…" canonical: "https://research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Inherent Disagreements in Human Textual Inferences](https://md.research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/) / cited by # Who cites «Inherent Disagreements in Human Textual Inferences» 240 papers of our library cite it (of the 140884 whose bibliographies we read) · 34 with a page here, the most cited first · page 1 of 2 · [← the paper](https://md.research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/) **1** [2](https://md.research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/cited-by/page/2/) - [Language (Technology) is Power: A Critical Survey of “Bias” in NLP](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/) — Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al. · 2020 · 1 700 citations - [Multitask Prompted Training Enables Zero-Shot Task Generalization](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/) — Victor Sanh, Albert Webson, Colin Raffel, et al. · 2021 · 1 577 citations - [CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models](https://md.research.elamur.ai/free/en/papers/nangia-2020-crows-pairs-challenge-dataset-measuring/) — Nikita Nangia, Clara Vania, Rasika Bhalerao, et al. · 2020 · 886 citations - [Whose Opinions Do Language Models Reflect?](https://md.research.elamur.ai/free/en/papers/santurkar-2023-whose-opinions-language-models-reflect/) — Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al. · 2023 · 390 citations - [Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection](https://md.research.elamur.ai/free/en/papers/sap-2022-annotators-attitudes-how-annotator-beliefs/) — Maarten Sap, Swabha Swayamdipta, Laura Vianna, et al. · 2022 · 364 citations - [The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation](https://md.research.elamur.ai/free/en/papers/plank-2022-problem-human-label-variation-ground/) — Barbara Plank · 2022 · 364 citations - [WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation](https://md.research.elamur.ai/free/en/papers/liu-2022-wanli-worker-ai-collaboration-natural/) — Alisa Liu, Swabha Swayamdipta, Noah A. 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