---
title: "Who cites Eve Fleisig — 201 papers of our library"
description: "201 papers of the Elamur Research library cite the works of Eve Fleisig, found in their bibliographies; the most cited first."
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---
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# Who cites Eve Fleisig

217 citations of their works from 201 papers of our library (of the 149,439 whose bibliographies we read) · 50 with a page here, the most cited first · [← Eve Fleisig](https://md.research.elamur.ai/free/en/authors/eve-fleisig/)

1. **[Bias and Fairness in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,082 citations*
2. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
3. [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
4. [**Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks arXiv:2306.07899**Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/veselovsky-2023-artificial-artificial-artificial-intelligence-crowd/)
5. [**Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text arXiv:2401.12070**Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/hans-2024-spotting-llms-binoculars-zero-shot/)
6. **[Quantifying the Persona Effect in LLM Simulations](https://md.research.elamur.ai/free/en/papers/hu-2024-quantifying-persona-effect-llm-simulations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tiancheng Hu, Nigel Collier*2024 · 116 citations*
7. **[RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors](https://md.research.elamur.ai/free/en/papers/dugan-2024-raid-shared-benchmark-robust-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liam Dugan, Alyssa Hwang, Filip Trhlík, et al.*2024 · 110 citations*
8. **[LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts](https://md.research.elamur.ai/free/en/papers/hashemi-2024-llm-rubric-multidimensional-calibrated-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Helia Hashemi, Jason Eisner, Corby Rosset, et al.*2024 · 88 citations*
9. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
10. **[People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated text](https://md.research.elamur.ai/free/en/papers/russell-2025-people-who-frequently-use-chatgpt/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jenna Russell, Marzena Karpinska, Mohit Iyyer*2025 · 33 citations*
11. **[Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions](https://md.research.elamur.ai/free/en/papers/orlikowski-2025-beyond-demographics-fine-tuning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Matthias Orlikowski, Jiaxin Pei, Paul Röttger, et al.*2025 · 22 citations*
12. **[Can Unconfident LLM Annotations Be Used for Confident Conclusions?](https://md.research.elamur.ai/free/en/papers/gligoric-2025-can-unconfident-llm-annotations-be/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kristina Gligorić, Tijana Zrnic, Cinoo Lee, et al.*2025 · 19 citations*
13. **[Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be Better](https://md.research.elamur.ai/free/en/papers/liu-2024-does-detectgpt-fully-utilize-perturbation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengchao Liu, Xiaoming Liu, Yichen Wang, et al.*2024 · 16 citations*
14. **[Natural Language Processing RELIES on Linguistics](https://md.research.elamur.ai/free/en/papers/opitz-2025-natural-language-processing-relies-linguistics/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Juri Opitz, Shira Wein, Nathan Schneider*2025 · 13 citations*
15. **[WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback](https://md.research.elamur.ai/free/en/papers/shi-2026-wildfeedback-aligning-llms-situ-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiwei Shi, Zhuoer Wang, Longqi Yang, et al.*2026 · 9 citations*
16. **[The Quest for the Right Mediator: Surveying Mechanistic Interpretability for NLP Through the Lens of Causal Mediation Analysis](https://md.research.elamur.ai/free/en/papers/mueller-2026-quest-right-mediator-surveying-mechanistic/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Aaron Mueller, Jannik Brinkmann, Millicent Li, et al.*2026 · 7 citations*
17. [**Generative AI and linguistic diversity in academic writing and publishing: Perspectives from World Englishes arXiv:2607.28505 · Generative AI and linguistic diversity in academic writing and publishing: Perspectives from World Englishes. Journal of English for Research Publication Purposes, 2025, 6(2), 265-289**Kingsley Ugwuanyi, Christian Mair, Sender Dovchin, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/ugwuanyi-2026-generative-ai-linguistic-diversity-academic/)
18. **[Finding A Voice: Exploring the Potential of African American Dialect and Voice Generation for Chatbots](https://md.research.elamur.ai/free/en/papers/finch-2025-finding-voice-exploring-potential-african/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sarah E. Finch, Ellie S. Paek, Ikseon Choi, et al.*2025 · 3 citations*
19. **[Trans-EnV: A Framework for Evaluating the Linguistic Robustness of LLMs Against English Varieties](https://md.research.elamur.ai/free/en/papers/lee-2025-trans-env-framework-evaluating-linguistic/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiyoung Lee, Seungho Kim, Jieun Han, et al.*2025 · 3 citations*
20. **[Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysis](https://md.research.elamur.ai/free/en/papers/xia-2026-explaining-generalization-ai-generated-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yuxi Xia, Kinga Stańczak, Benjamin Roth*2026 · 2 citations*
21. **[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*
22. **[Frankentext: Stitching random text fragments into long-form narratives](https://md.research.elamur.ai/free/en/papers/pham-2026-frankentext-stitching-random-text-fragments/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chau Minh Pham, Jenna Russell, Dzung Pham, et al.*2026 · 1 citation*
23. **[HARM: Learning Hate-Aware Reward Model for Evaluating Natural Language Explanations of Offensive Content](https://md.research.elamur.ai/free/en/papers/vecchi-2026-harm-learning-hate-aware-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lorenzo Puppi Vecchi, Alceu de Souza Britto Jr, Emerson Cabrera Paraiso, et al.*2026 · 1 citation*
24. **[Identifying Bias in Machine-generated Text Detection](https://md.research.elamur.ai/free/en/papers/stowe-2026-identifying-bias-machine-generated-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kevin Stowe, Svetlana Afanaseva, Rodolfo C. Raimundo, et al.*2026 · 1 citation*
25. **[Measuring Human Contribution in AI-Assisted Content Generation](https://md.research.elamur.ai/free/en/papers/xie-2026-measuring-human-contribution-ai-assisted/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yueqi Xie, Tao Qi, Jingwei Yi, et al.*2026 · 1 citation*
26. **[Modeling Annotator Disagreement with Demographic-Aware Experts and Synthetic Perspectives](https://md.research.elamur.ai/free/en/papers/xu-2026-modeling-annotator-disagreement-demographic-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinuo Xu, Veronica Derricks, Allison Earl, et al.*2026 · 1 citation*
27. **[No Shortcuts to Culture: Indonesian Multi-hop Question Answering for Complex Cultural Understanding](https://md.research.elamur.ai/free/en/papers/permadi-2026-no-shortcuts-culture-indonesian-multi/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vynska Amalia Permadi, Xingwei Tan, Nafise Sadat Moosavi, et al.*2026 · 1 citation*
28. **[Spotlights and Blindspots: Evaluating Machine-Generated Text Detection](https://md.research.elamur.ai/free/en/papers/stowe-2026-spotlights-blindspots-evaluating-machine-generated/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kevin Stowe, Kailash Patil*2026 · 1 citation*
29. **[Śmigiel Dataset: Laying Foundations for Investigating Machine-Generated Text Detection in Polish](https://md.research.elamur.ai/free/en/papers/strebeyko-2026-smigiel-dataset-laying-foundations-investigating/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jakub Strebeyko, Alina Wróblewska, Piotr Przybyła*2026 · 1 citation*
30. [**AI systems and the reproduction of (standard) language ideologies in World Englishes arXiv:2607.28528**Kingsley Ugwuanyi*2026*](https://md.research.elamur.ai/free/en/papers/ugwuanyi-2026-ai-systems-reproduction-standard-language/)
31. [**An Investigation of Linguistic Biases in LLM-Based Recommendations arXiv:2604.25456**Nitin Venkateswaran, Jason Ang, Deep Adhikari, et al.*2026*](https://md.research.elamur.ai/free/en/papers/venkateswaran-2026-investigation-linguistic-biases-llm-based/)
32. **[Can I guess where you are from? Modeling dialectal morphosyntactic similarities in Brazilian Portuguese](https://md.research.elamur.ai/free/en/papers/siqueira-2026-can-i-guess-where-you/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Manoel Siqueira, Raquel Freitag*2026*
33. **[CodeRipple: Wavelet-Based Detection of LLM-Generated Code](https://md.research.elamur.ai/free/en/papers/yao-2026-coderipple-wavelet-based-detection-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xingyu Yao, Zhendong Mao, Quan Wang*2026*
34. [**DialectLLM: A Dialect-Aware Dialogue Generation Framework Beyond Standard American English arXiv:2601.22888**Jio Oh, Paul Vicinanza, Thomas Butler, et al.*2026*](https://md.research.elamur.ai/free/en/papers/oh-2026-dialectllm-dialect-aware-dialog-ue/)
35. [**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/)
36. [**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/)
37. **[From a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale](https://md.research.elamur.ai/free/en/papers/abdullah-2026-river-gilead-inference-distributions-large/) [Proceedings of the AAAI/ACM Conference on AI Ethics and Society](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-acm-conference-on-ai-ethics-and-society/)**Chowdhury Mohammad Abdullah, Rita Orji*2026*
38. **[GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*2026*
39. **[GigaCheck: Detecting LLM-generated Content via Object-Centric Span Localization](https://md.research.elamur.ai/free/en/papers/tolstykh-2026-gigacheck-detecting-llm-generated-content/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Irina Tolstykh, Aleksandra Tsybina, Sergey Yakubson, et al.*2026*
40. [**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/)
41. **[Illusions of the Gold Standard: A Large-scale Analysis of Human Evaluation Protocols for Long-form Text Generation](https://md.research.elamur.ai/free/en/papers/mei-2026-illusions-gold-standard-large-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Katelyn X. Mei, Yi-Li Hsu, Minjoon Choi, et al.*2026*
42. **[KCLarity at SemEval-2026 Task 6: Encoder and Zero-Shot Approaches to Political Evasion Detection](https://md.research.elamur.ai/free/en/papers/sage-2026-kclarity-semeval-2026-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Archie Sage, Salvatore Greco*2026*
43. [**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/)
44. **[ORCA: Open-ended Response Correctness Assessment for Audio Question Answering](https://md.research.elamur.ai/free/en/papers/sedlacek-2026-orca-open-ended-response-correctness/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Šimon Sedláček, Sara Barahona, Cecilia Bolaños, et al.*2026*
45. **[SearchLLM: Detecting LLM Paraphrased Text by Measuring the Similarity with Regeneration of the Candidate Source via Search Engine](https://md.research.elamur.ai/free/en/papers/son-2026-searchllm-detecting-llm-paraphrased-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hoang-Quoc Nguyen-Son, Minh-Son Dao, Koji Zettsu*2026*
46. **[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*
47. [**Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs arXiv:2609.23955**Mai Mohamed Eida, Ryan Dolan, Paul de Nijs, et al.*2026*](https://md.research.elamur.ai/free/en/papers/eida-2026-some-dialects-more-equal-than/)
48. **[The Relevance of Value Systems for Offensive Language Detection](https://md.research.elamur.ai/free/en/papers/wiegand-2026-relevance-value-systems-offensive-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Michael Wiegand, Elisabeth Eder, Josef Ruppenhofer*2026*
49. **[When the Gold Standard Isn't Necessarily Standard: Challenges of Evaluating the Translation of User-Generated Content](https://md.research.elamur.ai/free/en/papers/nishimwe-2026-when-gold-standard-isn-t/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Lydia Nishimwe, Benoît Sagot, Rachel Bawden*2026*
50. [**Social Perceptions of English Spelling Variation on Twitter: A Comparative Analysis of Human and LLM Responses arXiv:2511.23041**Dong Nguyen, Laura Rosseel*2025*](https://md.research.elamur.ai/free/en/papers/nguyen-2025-social-perceptions-english-spelling-variation/)

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