---
title: "Who cites Nicole Meister — 120 papers of our library"
description: "120 papers of the Elamur Research library cite the works of Nicole Meister, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/nicole-meister/cited-by/"
---
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# Who cites Nicole Meister

120 citations of their works from 120 papers of our library (of the 149,439 whose bibliographies we read) · 33 with a page here, the most cited first · [← Nicole Meister](https://md.research.elamur.ai/free/en/authors/nicole-meister/)

1. **[Investigating Data Contamination in Modern Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*
2. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
3. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
4. [**Rethinking Benchmark and Contamination for Language Models with Rephrased Samples arXiv:2311.04850**Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-rethinking-benchmark-contamination-language-models/)
5. **[Task Contamination: Language Models May Not Be Few-Shot Anymore](https://md.research.elamur.ai/free/en/papers/li-2023-task-contamination-language-models-may/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Changmao Li, Jeffrey Flanigan*2023 · 89 citations*
6. [**Do Membership Inference Attacks Work on Large Language Models? arXiv:2402.07841**Michael Duan, Anshuman Suri, Niloofar Mireshghallah, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/duan-2024-membership-inference-attacks-work-large/)
7. [**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/)
8. **[MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks](https://md.research.elamur.ai/free/en/papers/ahuja-2024-megaverse-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.*2024 · 74 citations*
9. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
10. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.*2025 · 45 citations*
11. **[Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions](https://md.research.elamur.ai/free/en/papers/suh-2025-language-model-fine-tuning-scaled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joseph Suh, Erfan Jahanparast, Suhong Moon, et al.*2025 · 28 citations*
12. **[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*
13. **[“Seeing the Big through the Small”: Can LLMs Approximate Human Judgment Distributions on NLI from a Few Explanations?](https://md.research.elamur.ai/free/en/papers/chen-2024-seeing-big-through-small-can/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Xinpeng Wang, Siyao Peng, et al.*2024 · 18 citations*
14. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
15. **[Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges](https://md.research.elamur.ai/free/en/papers/samuel-2025-data-contamination-detection-modern-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Vinay Samuel, Yue Zhou, Henry Peng Zou*2025 · 16 citations*
16. **[Value Profiles for Encoding Human Variation](https://md.research.elamur.ai/free/en/papers/sorensen-2025-value-profiles-encoding-human-variation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Taylor Sorensen, Pushkar Mishra, Roma Patel, et al.*2025 · 15 citations*
17. **[Label and Explanation Variation in LLM-Based Annotation: a Case Study in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/kulmizev-2026-label-explanation-variation-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Artur Kulmizev, Erika Lombart, Patrick Watrin, et al.*2026 · 2 citations*
18. **[Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis](https://md.research.elamur.ai/free/en/papers/makhija-2026-neural-breadcrumbs-membership-inference-attacks/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Disha Makhija, Manoj Ghuhan Arivazhagan, Vinayshekhar Bannihatti Kumar, et al.*2026 · 2 citations*
19. **[When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation Evaluation](https://md.research.elamur.ai/free/en/papers/tan-2026-when-flores-bloomz-wrong-cross/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**David Tan, Pinzhen Chen, Josef van Genabith, et al.*2026 · 2 citations*
20. **[Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts](https://md.research.elamur.ai/free/en/papers/zheng-2026-beyond-value-benchmarks-measuring-value/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingting Zheng, Yuqi Ren, Linhao Yu, et al.*2026 · 1 citation*
21. **[Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-image-corruption-inspired-membership-inference/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zongyu Wu, Minhua Lin, Zhiwei Zhang, et al.*2026 · 1 citation*
22. [**MÖVE: A Holistic LLM Benchmark for the German Public Sector arXiv:2606.13111**Camilla Dalerci, Thilo Michael, Robin Schaefer, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/dalerci-2026-m-ove-holistic-llm-benchmark/)
23. **[The Pluralistic Moral Gap: Understanding Moral Judgment and Value Differences between Humans and Large Language Models](https://md.research.elamur.ai/free/en/papers/russo-2026-pluralistic-moral-gap-understanding-moral/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Giuseppe Russo, Debora Nozza, Paul Röttger, et al.*2026 · 1 citation*
24. **[Are LLM Benchmarks Already Contaminated? A Systematic Review of Contamination Detection Methods](https://md.research.elamur.ai/free/en/papers/nourbakhsh-2026-are-llm-benchmarks-already-contaminated/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Erfan Nourbakhsh, Mohammad Sadegh Sirjani, Amir Mousavi, et al.*2026*
25. **[Black-Box Membership Inference Attacks for Video Training Data in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-black-box-membership-inference-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinrui Wang, Zhenfeng Gao, Wendan Wang, et al.*2026*
26. **[Controllable Contamination Detection for Reliable LLM Evaluation with Statistical Guarantees](https://md.research.elamur.ai/free/en/papers/zhang-2026-controllable-contamination-detection-reliable-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Zhang, Qi Liu, Siyuan Liang, et al.*2026*
27. **[Distributional Alignment for Large Language Models under Domain Shift](https://md.research.elamur.ai/free/en/papers/pham-2026-distributional-alignment-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Thanh Pham, Lizhen Qu, Zhuang Li, et al.*2026*
28. **[JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/shi-2026-judgeagent-beyond-static-benchmarks-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhichao Shi, Xuhui Jiang, Chengjin Xu, et al.*2026*
29. **[Memory Dial: A Training Framework for Controllable Memorization in Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-memory-dial-training-framework-controllable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangbo Zhang, Ali Emami*2026*
30. **[PDR: A Plug-and-Play Positional Decay Framework for LLM Pre-training Data Detection](https://md.research.elamur.ai/free/en/papers/liu-2026-pdr-plug-play-positional-decay/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhan Liu, Yibo Yang, Ruiying Lu, et al.*2026*
31. **[SPENCE: A Syntactic Probe for Detecting Contamination in NL2SQL Benchmarks](https://md.research.elamur.ai/free/en/papers/safarzadeh-2026-spence-syntactic-probe-detecting-contamination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohammadtaher Safarzadeh, Hitesh Laxmichand Patel, Afshin Oroojlooy, et al.*2026*
32. **[Thesis Proposal: Intentional Inference for Insight Generation](https://md.research.elamur.ai/free/en/papers/onderkova-2026-thesis-proposal-intentional-inference-insight/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kristýna Onderková*2026*
33. **[Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation](https://md.research.elamur.ai/free/en/papers/ma-2026-too-open-opinion-embracing-open/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bolei Ma, Yong Cao, Indira Sen, et al.*2026*

87 more citing papers of our library have no page here yet.

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