---
title: "Who cites Valerie Chen — 94 papers of our library"
description: "94 papers of the Elamur Research library cite the works of Valerie Chen, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/valerie-chen/cited-by/"
---
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# Who cites Valerie Chen

113 citations of their works from 94 papers of our library (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · [← Valerie Chen](https://md.research.elamur.ai/free/en/authors/valerie-chen/)

1. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
2. **[Investigating Cultural Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-investigating-cultural-alignment-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Badr AlKhamissi, Muhammad ElNokrashy, Mai Alkhamissi, et al.*2024 · 183 citations*
3. **[“My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-my-answer-is-c-first/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinpeng Wang, Bolei Ma, Chengzhi Hu, et al.*2024 · 91 citations*
4. **[The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct Representation](https://md.research.elamur.ai/free/en/papers/pavlovic-2024-effectiveness-llms-annotators-comparative-overview/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Maja Pavlovic, Massimo Poesio*2024 · 49 citations*
5. **[Beyond Prompt Brittleness: Evaluating the Reliability and Consistency of Political Worldviews in LLMs](https://md.research.elamur.ai/free/en/papers/ceron-2024-beyond-prompt-brittleness-evaluating-reliability/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tanise Ceron, Neele Falk, Ana Barić, et al.*2024 · 46 citations*
6. **[“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*
7. **[A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
8. **[Scaling Collaborative Effort with Agents](https://md.research.elamur.ai/free/en/papers/shen-2026-scaling-collaborative-effort-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shannon Zejiang Shen, Valerie Chen, Ken Gu, et al.*2026 · 7 citations*
9. **[Don't Trust Generative Agents to Mimic Communication on Social Networks Unless You Benchmarked their Empirical Realism](https://md.research.elamur.ai/free/en/papers/munker-2026-don-t-trust-generative-agents/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Simon Münker, Nils Schwager, Achim Rettinger*2026 · 4 citations*
10. **[Comparing Moral Values in Western English-speaking societies and LLMs with Word Associations](https://md.research.elamur.ai/free/en/papers/xiang-2025-comparing-moral-values-western-english/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoyi Xiang, Chunhua Liu, Simon De Deyne, et al.*2025 · 3 citations*
11. **[Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?](https://md.research.elamur.ai/free/en/papers/molfetta-2026-sycophants-courtroom-are-llms-fragile/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.*2026 · 2 citations*
12. **[German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies](https://md.research.elamur.ai/free/en/papers/rupprecht-2026-german-general-social-survey-personas/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jens Rupprecht, Leon Froehling, Claudia Wagner, et al.*2026 · 1 citation*
13. **[Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-Judge](https://md.research.elamur.ai/free/en/papers/sun-2026-label-effects-shared-heuristic-reliance/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Sun, Di Wu, Sijing Qin, et al.*2026 · 1 citation*
14. **[Prompt Perturbations Reveal Human-Like Biases in Large Language Model Survey Responses](https://md.research.elamur.ai/free/en/papers/rupprecht-2026-prompt-perturbations-reveal-human-like/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Jens Rupprecht, Georg Ahnert, Markus Strohmaier*2026 · 1 citation*
15. **[Sense and Sensitivity: “Reasoning” Models are More Robust, but can Diverge from Human Consensus in a Legal Interpretation Task](https://md.research.elamur.ai/free/en/papers/petersen-2026-sense-sensitivity-reasoning-models-are/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Dawson Petersen, Abhishek Purushothama, Nathan Schneider*2026 · 1 citation*
16. **[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*
17. **[The Thin Line Between Comprehension and Persuasion in LLMs](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrian de Wynter, Tangming Yuan*2026 · 1 citation*
18. **[Uncertainty Quantification for Evaluating Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/staliunaite-2026-uncertainty-quantification-evaluating-gender-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ieva Staliunaite, Julius Cheng, Andreas Vlachos*2026 · 1 citation*
19. **[Challenging the Myth: A Research Arc on LLMs as Human Simulacra](https://md.research.elamur.ai/free/en/papers/munker-2026-challenging-myth-research-arc-llms/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Simon Münker, Achim Rettinger, Damian Trilling*2026*
20. **[Simulating Social Attitudes with LLMs: Accuracy, Demographic Effects, and Refusal Behavior in the Sensitive Domain of Suicide Prevention](https://md.research.elamur.ai/free/en/papers/perez-2026-simulating-social-attitudes-llms-accuracy/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Cristina J. Perez, Michael P. Vasquez Jr, Philippe Giabbanelli, et al.*2026*
21. [**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/)

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

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