mlsanityData to 7 Oct 2026

Tracking the perspectives of interacting language models

arXiv 2406.11938 ↗First posted 17 Jun 2024cs.AI cs.MAcited by 14

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Abstract (arXiv)

Large language models (LLMs) are capable of producing high quality information at unprecedented rates. As these models continue to entrench themselves in society, the content they produce will become increasingly pervasive in databases that are, in turn, incorporated into the pre-training data, fine-tuning data, retrieval data, etc. of other language models. In this paper we formalize the idea of a communication network of LLMs and introduce a method for representing the perspective of individual models within a collection of LLMs. Given these tools we systematically study information diffusion in the communication network of LLMs in various simulated settings.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 28 of its 45 references that are in the map. First posted on arXiv 17 Jun 2024.

Builds on

28 of 45 references.

References · 28

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2023GPT-4 Technical Reportcited by 18,132
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  10. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,201
  11. 2023Pythia: A Suite for Analyzing Large Language Models Across Training and Scalingcited by 1,734
  12. 2022Make-A-Video: Text-to-Video Generation without Text-Video Datacited by 1,725
16 more
  1. 2020MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformerscited by 1,414
  2. 2018Taskonomy: Disentangling Task Transfer Learningcited by 631
  3. 2023The Curse of Recursion: Training on Generated Data Makes Models Forgetcited by 343
  4. 2024Nomic Embed: Training a Reproducible Long Context Text Embeddercited by 255
  5. 2023Evaluating Large Language Models in Theory of Mind Taskscited by 217
  6. 2023Simulating Opinion Dynamics with Networks of LLM-based Agentscited by 153
  7. 2023Machine Culturecited by 55
  8. 2024Network Formation and Dynamics Among Multi-LLMscited by 28
  9. 2019GraSPy: Graph Statistics in Pythoncited by 15
  10. 2023Comparing Foundation Models using Data Kernelscited by 14
  11. 2021Towards a theory of out-of-distribution learningcited by 11
  12. 2018Out-of-sample extension of graph adjacency spectral embeddingcited by 8
  13. 2023A Statistical Turing Test for Generative Modelscited by 8
  14. 2022Mental State Classification Using Multi-graph Featurescited by 7
  15. 2020A partition-based similarity for classification distributionscited by 6
  16. 2021Dynamic Silos: Increased Modularity in Intra-organizational Communication Networks during the Covid-19 Pandemiccited by 3

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Citing papers per year: 2024: 4; 2025: 6; 2026: 4.

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