---
title: "Who cites Lisa Green — 193 papers of our library"
description: "193 papers of the Elamur Research library cite the works of Lisa Green, found in their bibliographies; the most cited first."
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---
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# Who cites Lisa Green

200 citations of their works from 193 papers of our library (of the 149,439 whose bibliographies we read) · 60 with a page here, the most cited first · [← Lisa Green](https://md.research.elamur.ai/free/en/authors/lisa-green/)

1. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,716 citations*
3. **[RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models](https://md.research.elamur.ai/free/en/papers/gehman-2020-realtoxicityprompts-evaluating-neural-toxic-degeneration/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Samuel Gehman, Suchin Gururangan, Maarten Sap, et al.*2020 · 1,306 citations*
4. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
5. **[The Risk of Racial Bias in Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/sap-2019-risk-racial-bias-hate-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maarten Sap, Dallas Card, Saadia Gabriel, et al.*2019 · 1,164 citations*
6. **[Social Bias Frames: Reasoning about Social and Power Implications of Language](https://md.research.elamur.ai/free/en/papers/sap-2020-social-bias-frames-reasoning-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Maarten Sap, Saadia Gabriel, Lianhui Qin, et al.*2020 · 684 citations*
7. **[Racial Bias in Hate Speech and Abusive Language Detection Datasets](https://md.research.elamur.ai/free/en/papers/davidson-2019-racial-bias-hate-speech-abusive/) [Workshop on Abusive Language Online](https://md.research.elamur.ai/free/en/venues/workshop-on-abusive-language-online/)**Thomas Davidson, Debasmita Bhattacharya, Ingmar Weber*2019 · 583 citations*
8. **[Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems](https://md.research.elamur.ai/free/en/papers/kiritchenko-2018-examining-gender-race-bias-two/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Svetlana Kiritchenko, Saif Mohammad*2018 · 579 citations*
9. **[Style Transfer Through Back-Translation](https://md.research.elamur.ai/free/en/papers/prabhumoye-2018-style-transfer-through-back-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, et al.*2018 · 558 citations*
10. **[Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection](https://md.research.elamur.ai/free/en/papers/ravfogel-2020-null-it-out-guarding-protected/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shauli Ravfogel, Yanai Elazar, Hila Gonen, et al.*2020 · 488 citations*
11. [**Ethical and social risks of harm from Language Models arXiv:2112.04359**Laura Weidinger, John Mellor, Maribeth Rauh, et al.*2021 · 456 citations*](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/)
12. **[Gender and Dialect Bias in YouTube's Automatic Captions](https://md.research.elamur.ai/free/en/papers/tatman-2017-gender-dialect-bias-youtube-s/) [ACL Workshop on Ethics in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/acl-workshop-on-ethics-in-natural-language-processing/)**Rachael Tatman*2017 · 423 citations*
13. **[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/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Maarten Sap, Swabha Swayamdipta, Laura Vianna, et al.*2022 · 367 citations*
14. **[Adversarial Removal of Demographic Attributes from Text Data](https://md.research.elamur.ai/free/en/papers/elazar-2018-adversarial-removal-demographic-attributes-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yanai Elazar, Yoav Goldberg*2018 · 359 citations*
15. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 350 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
16. **[Hate Speech Detection and Racial Bias Mitigation in Social Media based on BERT model](https://md.research.elamur.ai/free/en/papers/mozafari-2020-hate-speech-detection-racial-bias/) [PLoS ONE](https://md.research.elamur.ai/free/en/venues/plos-one/)**Marzieh Mozafari, Reza Farahbakhsh, Noel Crespi*2020 · 305 citations*
17. **[The Importance of Modeling Social Factors of Language: Theory and Practice](https://md.research.elamur.ai/free/en/papers/hovy-2021-importance-modeling-social-factors-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dirk Hovy, Diyi Yang*2021 · 238 citations*
18. **[Challenges in Detoxifying Language Models](https://md.research.elamur.ai/free/en/papers/welbl-2021-challenges-detoxifying-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Johannes Welbl, Amelia Glaese, Jonathan Uesato, et al.*2021 · 213 citations*
19. **[Challenges in Automated Debiasing for Toxic Language Detection](https://md.research.elamur.ai/free/en/papers/zhou-2021-challenges-automated-debiasing-toxic-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Xuhui Zhou, Maarten Sap, Swabha Swayamdipta, et al.*2021 · 191 citations*
20. **[Mapping the Americanization of English in Space and Time](https://md.research.elamur.ai/free/en/papers/gon-ccalves-2017-mapping-americanization-english-space-time/) [PLoS ONE](https://md.research.elamur.ai/free/en/venues/plos-one/)**Bruno Gonçalves, Lucia Loureiro-Porto, Jose J. Ramasco, et al.*2017 · 157 citations*
21. **[Measure and Improve Robustness in NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xuezhi Wang, Haohan Wang, Diyi Yang*2022 · 148 citations*
22. **[The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization](https://md.research.elamur.ai/free/en/papers/pilan-2022-text-anonymization-benchmark-tab-dedicated/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ildikó Pilán, Pierre Lison, Lilja Øvrelid, et al.*2022 · 131 citations*
23. **[Overcoming Language Variation in Sentiment Analysis with Social Attention](https://md.research.elamur.ai/free/en/papers/yang-2017-overcoming-language-variation-sentiment-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yi Yang, Jacob Eisenstein*2017 · 119 citations*
24. [**Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English arXiv:1707.00061**Su Lin Blodgett, Brendan O'Connor*2017 · 105 citations*](https://md.research.elamur.ai/free/en/papers/blodgett-2017-racial-disparity-natural-language-processing/)
25. **[Investigating African-American Vernacular English in Transformer-Based Text Generation](https://md.research.elamur.ai/free/en/papers/groenwold-2020-investigating-african-american-vernacular-english/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sophie Groenwold, Lily Ou, Aesha Parekh, et al.*2020 · 99 citations*
26. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
27. [**Twitter Universal Dependency Parsing for African-American and Mainstream American English**Su Lin Blodgett, Johnny Wei, Brendan O'Connor*2018 · 92 citations*](https://md.research.elamur.ai/free/en/papers/blodgett-2018-twitter-universal-dependency-parsing-african/)
28. [**VALUE: Understanding Dialect Disparity in NLU**Caleb Ziems, Jiaao Chen, Camille Harris, et al.*2022 · 67 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2022-value-understanding-dialect-disparity-nlu/)
29. **[Arabic Dialect Identification in the Context of Bivalency and Code-Switching](https://md.research.elamur.ai/free/en/papers/haj-2018-arabic-dialect-identification-context-bivalency/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mahmoud El-Haj, Paul Rayson, Mariam Aboelezz*2018 · 60 citations*
30. [**Dialect prejudice predicts AI decisions about people's character, employability, and criminality arXiv:2403.00742**Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-2024-dialect-prejudice-predicts-ai-decisions/)
31. **[Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception](https://md.research.elamur.ai/free/en/papers/lin-2025-investigating-bias-llm-based-bias/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Luyang Lin, Lingzhi Wang, Jinsong Guo, et al.*2025 · 44 citations*
32. **[Paloma: A Benchmark for Evaluating Language Model Fit](https://md.research.elamur.ai/free/en/papers/magnusson-2023-paloma-benchmark-evaluating-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ian Magnusson, Akshita Bhagia, Valentin Hofmann, et al.*2023 · 42 citations*
33. **[Sociodemographic Bias in Language Models: A Survey and Forward Path](https://md.research.elamur.ai/free/en/papers/gupta-2023-sociodemographic-bias-language-models-survey/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Vipul Gupta, Pranav Narayanan Venkit, Shomir Wilson, et al.*2023 · 40 citations*
34. [**Mitigating Racial Biases in Toxic Language Detection with an Equity-Based Ensemble Framework arXiv:2109.13137**Matan Halevy, Camille Harris, Amy Bruckman, et al.*2021 · 38 citations*](https://md.research.elamur.ai/free/en/papers/halevy-2021-mitigating-racial-biases-toxic-language/)
35. **[A Dataset and Classifier for Recognizing Social Media English](https://md.research.elamur.ai/free/en/papers/blodgett-2017-dataset-classifier-recognizing-social-media/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Su Lin Blodgett, Johnny Wei, Brendan O'Connor*2017 · 36 citations*
36. **[Towards a Deep Multi-layered Dialectal Language Analysis: A Case Study of African-American English](https://md.research.elamur.ai/free/en/papers/dacon-2022-deep-multi-layered-dialectal-language/) [Workshop on Bridging Human–Computer Interaction and Natural Language Processing](https://md.research.elamur.ai/free/en/venues/hcinlp/)**Jamell Dacon*2022 · 13 citations*
37. **[Corpus-Guided Contrast Sets for Morphosyntactic Feature Detection in Low-Resource English Varieties](https://md.research.elamur.ai/free/en/papers/masis-2022-corpus-guided-contrast-sets-morphosyntactic/) [Workshop on NLP Applications to Field Linguistics](https://md.research.elamur.ai/free/en/venues/fieldmatters/)**Tessa Masis, Anissa Neal, Lisa Green, et al.*2022 · 10 citations*
38. **[Perceptions of Language Technology Failures from South Asian English Speakers](https://md.research.elamur.ai/free/en/papers/holt-2024-perceptions-language-technology-failures-south/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Faye Holt, William Held, Diyi Yang*2024 · 9 citations*
39. [**A Comprehensive View of the Biases of Toxicity and Sentiment Analysis Methods Towards Utterances with African American English Expressions arXiv:2401.12720**Guilherme H. Resende, Luiz F. Nery, Fabricio Benevenuto, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/resende-2024-comprehensive-view-biases-toxicity-sentiment/)
40. **[Towards Augmenting Lexical Resources for Slang and African American English](https://md.research.elamur.ai/free/en/papers/hwang-2020-augmenting-lexical-resources-slang-african/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Alyssa Hwang, William R. Frey, Kathleen McKeown*2020 · 8 citations*
41. **[Analyzing Dialectical Biases in LLMs for Knowledge and Reasoning Benchmarks](https://md.research.elamur.ai/free/en/papers/pan-2025-analyzing-dialectical-biases-llms-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Eileen Pan, Anna Seo Gyeong Choi, Maartje Ter Hoeve, et al.*2025 · 6 citations*
42. **[Evaluating and Mitigating Inherent Linguistic Bias of African American English through Inference](https://md.research.elamur.ai/free/en/papers/dacon-2022-evaluating-mitigating-inherent-linguistic-bias/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jamell Dacon, Haochen Liu, Jiliang Tang*2022 · 6 citations*
43. **[Analysis of LLM as a grammatical feature tagger for African American English](https://md.research.elamur.ai/free/en/papers/porwal-2025-analysis-llm-as-grammatical-feature/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rahul Porwal, Alice Rozet, Jotsna Gowda, et al.*2025 · 4 citations*
44. **[Leveraging Syntactic Dependencies in Disambiguation: The Case of African American English](https://md.research.elamur.ai/free/en/papers/previlon-2024-leveraging-syntactic-dependencies-disambiguation-case/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Wilermine Previlon, Alice Rozet, Jotsna Gowda, et al.*2024 · 4 citations*
45. **[My LLM might Mimic AAE - But When Should It?](https://md.research.elamur.ai/free/en/papers/sandoval-2025-my-llm-might-mimic-aae/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sandra Camille Sandoval, Christabel Acquaye, Kwesi Adu Cobbina, et al.*2025 · 3 citations*
46. **[Attention to Non-Adopters](https://md.research.elamur.ai/free/en/papers/zhou-2026-attention-non-adopters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaitlyn Zhou, Kristina Gligorić, Myra Cheng, et al.*2026 · 1 citation*
47. **[Cultural Benchmarking of LLMs in Standard and Dialectal Arabic Dialogues](https://md.research.elamur.ai/free/en/papers/kautsar-2026-cultural-benchmarking-llms-standard-dialectal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Muhammad Dehan Al Kautsar, Saeed Almheiri, Momina Ahsan, et al.*2026 · 1 citation*
48. **[Modeling Cultural and Subcultural Variation in Code-Switched Discourse with Topic Annotation](https://md.research.elamur.ai/free/en/papers/tyagi-2026-modeling-cultural-subcultural-variation-code/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Nemika Tyagi, Nelvin Licona-Guevara, Olga Kellert*2026 · 1 citation*
49. [**Reinforcing Stereotypes of Anger: Emotion AI on African American Vernacular English arXiv:2511.10846**Rebecca Dorn, Christina Chance, Casandra Rusti, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dorn-2025-reinforcing-stereotypes-anger-emotion-ai/)
50. **[OLEA: Tool and Infrastructure for Offensive Language Error Analysis in English](https://md.research.elamur.ai/free/en/papers/grace-2023-olea-tool-infrastructure-offensive-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Marie Grace, Jay Seabrum, Dananjay Srinivas, et al.*2023 · 1 citation*
51. **[DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects](https://md.research.elamur.ai/free/en/papers/lucas-2026-dia-harm-dialectal-disparities-harmful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jason S Lucas, Matt Murtagh White, Ali Al-Lawati, et al.*2026*
52. **[Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual Data](https://md.research.elamur.ai/free/en/papers/schuler-2026-dialectal-filtering-synthesizing-kurdish-corpora/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Christian Schuler, Raman Ahmad, Ānrán Wáng, et al.*2026*
53. [**DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation arXiv:2607.07669**Jordan Painter, Dipankar Srirag, Adarsh Kappiyath, et al.*2026*](https://md.research.elamur.ai/free/en/papers/painter-2026-diallm-investigation-robustness-generation-gap/)
54. [**Evaluating the Usage of African-American Vernacular English in Large Language Models arXiv:2602.21485**Deja Dunlap, R. Thomas McCoy*2026*](https://md.research.elamur.ai/free/en/papers/dunlap-2026-evaluating-usage-african-american-vernacular/)
55. [**How Does "English (US)" Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline arXiv:2604.04204**Mir Tafseer Nayeem, Davood Rafiei*2026*](https://md.research.elamur.ai/free/en/papers/nayeem-2026-english-us-become-default-triangulating/)
56. [**LLMs Silently Correct African American English: Auditing and Mitigating Dialect Bias via Activation Steering arXiv:2607.06845**Huan Wu, Ali Emami, Muhammad Furquan Hassan, et al.*2026*](https://md.research.elamur.ai/free/en/papers/wu-2026-llms-silently-correct-african-american/)
57. **[Side-by-side Comparison Amplifies Dialect Bias in Language Models](https://md.research.elamur.ai/free/en/papers/kondapally-2026-side-side-comparison-amplifies-dialect/) [ACM Conference on Fairness, Accountability, and Transparency (FAccT)](https://md.research.elamur.ai/free/en/venues/acm-conference-on-fairness-accountability-and-transparency-facct/)**Kritee Kondapally, Claire J. Smerdon, Pooja C. Patel, et al.*2026*
58. [**How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models arXiv:2511.06676**Subhojit Ghimire*2025*](https://md.research.elamur.ai/free/en/papers/ghimire-2025-ai-fails-interactive-pedagogical-tool/)
59. [**Experiences from Creating a Benchmark for Sentiment Classification for Varieties of English arXiv:2410.11216**Dipankar Srirag, Jordan Painter, Aditya Joshi, et al.*2024*](https://md.research.elamur.ai/free/en/papers/srirag-2024-experiences-creating-benchmark-sentiment-classification/)
60. [**System Demo: Tool and Infrastructure for Offensive Language Error Analysis (OLEA) in English arXiv:2210.16398**Marie Grace, Xajavion "Jay" Seabrum, Dananjay Srinivas, et al.*2022*](https://md.research.elamur.ai/free/en/papers/grace-2022-system-demo-tool-infrastructure-offensive/)

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