mlsanityData to 7 Oct 2026

One world, one opinion? The superstar effect in LLM responses

arXiv 2412.10281 ↗First posted 13 Dec 2024cs.CLcited by 5

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Abstract (arXiv)

As large language models (LLMs) are shaping the way information is shared and accessed online, their opinions have the potential to influence a wide audience. This study examines who the LLMs view as the most prominent figures across various fields, using prompts in ten different languages to explore the influence of linguistic diversity. Our findings reveal low diversity in responses, with a small number of figures dominating recognition across languages (also known as the "superstar effect"). These results highlight the risk of narrowing global knowledge representation when LLMs retrieve subjective information.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 19 of its 48 references that are in the map. First posted on arXiv 13 Dec 2024.

Builds on

19 of 48 references.

References · 19

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2024The Llama 3 Herd of Modelscited by 14,192
  3. 2023Towards Measuring the Representation of Subjective Global Opinions in Language Modelscited by 424
  4. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  5. 2023MEGA: Multilingual Evaluation of Generative AIcited by 291
  6. 2022Challenges and Strategies in Cross-Cultural NLPcited by 216
  7. 2023Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Studycited by 203
  8. 2023Does Writing with Language Models Reduce Content Diversity?cited by 190
  9. 2023Generative artificial intelligence enhances creativity but reduces the diversity of novel contentcited by 165
  10. 2024A Note on Shumailov et al. (2024): `AI Models Collapse When Trained on Recursively Generated Data'cited by 114
  11. 2022Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?cited by 89
  12. 2022Extracting Cultural Commonsense Knowledge at Scalecited by 76
7 more
  1. 2023Ethical Reasoning over Moral Alignment: A Case and Framework for In-Context Ethical Policies in LLMscited by 64
  2. 2023MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Taskscited by 57
  3. 2024Large Language Models Reflect the Ideology of their Creatorscited by 56
  4. 2024LLMs Beyond English: Scaling the Multilingual Capability of LLMs with Cross-Lingual Feedbackcited by 51
  5. 2024PARIKSHA: A Large-Scale Investigation of Human-LLM Evaluator Agreement on Multilingual and Multi-Cultural Datacited by 37
  6. 2024Decoding Multilingual Moral Preferences: Unveiling LLM's Biases Through the Moral Machine Experimentcited by 11
  7. 2024Large Language Models as Evaluators for Scientific Synthesiscited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025The Basic B*** Effect: The Use of LLM-based Agents Reduces the Distinctiveness and Diversity of People's Choicescited by 5
  2. 2026Ambiguity Collapse by LLMs: A Taxonomy of Epistemic Riskscited by 3
  3. 2025Cash or Comfort? How LLMs Value Your Inconveniencecited by 1
  4. 2026LLM Consumer Behavior Theory: Foundations of a Novel Research Fieldcited by 0
  5. 2026On Epistemic Diversity in Large Language Modelscited by 0