🧑‍🔬 Who cites Lindia Tjuatja

120 citations of their works from 113 papers of our library (of the 149,439 whose bibliographies we read) · 27 with a page here, the most cited first · ← Lindia Tjuatja

1. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 189 citations
2. Investigating Cultural Alignment of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Badr AlKhamissi, Muhammad ElNokrashy, Mai Alkhamissi, et al.2024 · 183 citations
3. Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey DesignTransactions of the Association for Computational Linguistics (TACL)Lindia Tjuatja, Valerie Chen, Tongshuang Wu, et al.2024 · 140 citations
4. “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language ModelsFindings of the Association for Computational LinguisticsXinpeng Wang, Bolei Ma, Chengzhi Hu, et al.2024 · 91 citations
5. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
6. The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct RepresentationLanguage Resources and Evaluation Conference (LREC)Maja Pavlovic, Massimo Poesio2024 · 49 citations
7. Beyond Prompt Brittleness: Evaluating the Reliability and Consistency of Political Worldviews in LLMsTransactions of the Association for Computational Linguistics (TACL)Tanise Ceron, Neele Falk, Ana Barić, et al.2024 · 46 citations
8. “Seeing the Big through the Small”: Can LLMs Approximate Human Judgment Distributions on NLI from a Few Explanations?Findings of the Association for Computational LinguisticsBeiduo Chen, Xinpeng Wang, Siyao Peng, et al.2024 · 18 citations
9. A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLIFindings of the Association for Computational LinguisticsBeiduo Chen, Siyao Peng, Anna Korhonen, et al.2025 · 9 citations
10. Manipulating language models' training data to study syntactic constraint learning: the case of English passivizationarXiv:2407.04593Cara Su-Yi Leong, Tal Linzen2024 · 8 citations
11. Don't Trust Generative Agents to Mimic Communication on Social Networks Unless You Benchmarked their Empirical RealismConference of the European Chapter of the Association for Computational Linguistics (EACL)Simon Münker, Nils Schwager, Achim Rettinger2026 · 4 citations
12. Generating Difficult-to-Translate TextsWorkshop on Multilingual Multicultural EvaluationVilém Zouhar, Wenda Xu, Parker Riley, et al.2026 · 3 citations
13. Comparing Moral Values in Western English-speaking societies and LLMs with Word AssociationsAnnual Meeting of the Association for Computational Linguistics (ACL)Chaoyi Xiang, Chunhua Liu, Simon De Deyne, et al.2025 · 3 citations
14. Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?Annual Meeting of the Association for Computational Linguistics (ACL)Lorenzo Molfetta, Alessio Cocchieri, Luca Ragazzi, et al.2026 · 2 citations
15. A Review of Incorporating Psychological Theories in LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zizhou Liu, Ziwei Gong, Lin Ai, et al.2026 · 1 citation
16. German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM StudiesLanguage Resources and Evaluation Conference (LREC)Jens Rupprecht, Leon Froehling, Claudia Wagner, et al.2026 · 1 citation
17. Label Effects: Shared Heuristic Reliance in Trust Assessment by Humans and LLM-as-a-JudgeAnnual Meeting of the Association for Computational Linguistics (ACL)Xin Sun, Di Wu, Sijing Qin, et al.2026 · 1 citation
18. Prompt Perturbations Reveal Human-Like Biases in Large Language Model Survey ResponsesWorkshop on Natural Language Processing and Computational Social ScienceJens Rupprecht, Georg Ahnert, Markus Strohmaier2026 · 1 citation
19. Sense and Sensitivity: “Reasoning” Models are More Robust, but can Diverge from Human Consensus in a Legal Interpretation TaskConference on Computational Natural Language Learning (CoNLL)Dawson Petersen, Abhishek Purushothama, Nathan Schneider2026 · 1 citation
20. Surprisal and Metaphor Novelty Judgments: Moderate Correlations and Divergent Scaling Effects Revealed by Corpus-Based and Synthetic DatasetsConference of the European Chapter of the Association for Computational Linguistics (EACL)Omar Momen, Emilie Sitter, Berenike Herrmann, et al.2026 · 1 citation
21. The Pluralistic Moral Gap: Understanding Moral Judgment and Value Differences between Humans and Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Giuseppe Russo, Debora Nozza, Paul Röttger, et al.2026 · 1 citation
22. The Thin Line Between Comprehension and Persuasion in LLMsFindings of the Association for Computational LinguisticsAdrian de Wynter, Tangming Yuan2026 · 1 citation
23. Uncertainty Quantification for Evaluating Gender Bias in Machine TranslationFindings of the Association for Computational LinguisticsIeva Staliunaite, Julius Cheng, Andreas Vlachos2026 · 1 citation
24. Challenging the Myth: A Research Arc on LLMs as Human SimulacraBig Picture v2: Crafting a Research NarrativeSimon Münker, Achim Rettinger, Damian Trilling2026
25. Interlinear Glosses as a Multilingual Pivot for Machine Translation: An Updated Study on Turkish with Restricted ResourcesSIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered LanguagesVolkan Ozer, Shu Okabe, Alexander Fraser2026
26. Simulating Social Attitudes with LLMs: Accuracy, Demographic Effects, and Refusal Behavior in the Sensitive Domain of Suicide PreventionWorkshop on Natural Language Processing and Computational Social ScienceCristina J. Perez, Michael P. Vasquez Jr, Philippe Giabbanelli, et al.2026
27. Social Perceptions of English Spelling Variation on Twitter: A Comparative Analysis of Human and LLM ResponsesarXiv:2511.23041Dong Nguyen, Laura Rosseel2025

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