Large Language Model (German Wikipedia)

Analysis of information sources in references of the Wikipedia article "Large Language Model" in German language version.

Last modified:

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abcnews.com (Global: 4,537th place; German: low place)

aclweb.org (Global: low place; German: low place)

  • Alessio Miaschi et al.: What Makes My Model Perplexed? A Linguistic Investigation on Neural Language Models Perplexity. Association for Computational Linguistics, 2021, S. 40–47, doi:10.18653/v1/2021.deelio-1.5 (englisch, aclweb.org [abgerufen am 17. April 2026]).

acm.org (Global: 1,200th place; German: 2,201st place)

dl.acm.org

  • Shriyank Somvanshi et al.: From Tiny Machine Learning to Tiny Deep Learning: A Survey. In: ACM Computing Surveys. Band 58, Nr. 7, 24. Dezember 2025, ISSN 0360-0300, S. 1–33, doi:10.1145/3776588 (englisch, acm.org [abgerufen am 5. April 2026]).

ai.mil (Global: low place; German: low place)

  • CDAO. Abgerufen am 1. April 2026 (englisch).

aifactum.de (Global: low place; German: low place)

aip.org (Global: 2,273rd place; German: 3,403rd place)

pubs.aip.org

  • F. Jelinek et al.: Perplexity—a measure of the difficulty of speech recognition tasks. In: The Journal of the Acoustical Society of America. Band 62, S1, 1. Dezember 1977, ISSN 0001-4966, S. S63–S63, doi:10.1121/1.2016299 (englisch, aip.org [abgerufen am 17. April 2026]).

amacad.org (Global: 2,591st place; German: 940th place)

apnews.com (Global: 101st place; German: 386th place)

apxml.com (Global: low place; German: low place)

arena.ai (Global: low place; German: low place)

arxiv.org (Global: 49th place; German: 152nd place)

azure.com (Global: low place; German: low place)

ai.azure.com

bentoml.com (Global: low place; German: low place)

bigdata-insider.de (Global: low place; German: low place)

  • Nico Litzel, Stefan Luber: Was ist BERT? In: Bigdata Insider. Vogel Communications Group, 10. Mai 2022, abgerufen am 8. November 2025.

brennancenter.org (Global: low place; German: low place)

claude.com (Global: low place; German: low place)

support.claude.com

platform.claude.com

cmu.edu (Global: 2,125th place; German: 3,522nd place)

kilthub.cmu.edu

  • Stanley F Chen et al.: Evaluation Metrics For Language Models. 30. Juni 2018, doi:10.1184/R1/6605324.V1 (englisch, cmu.edu [abgerufen am 17. April 2026]).

computer.org (Global: 6,549th place; German: low place)

datascientest.com (Global: low place; German: low place)

decrypt.co (Global: low place; German: low place)

derstandard.de (Global: 4,676th place; German: 299th place)

djdumpling.github.io (Global: low place; German: low place)

doi.org (Global: 2nd place; German: 3rd place)

  • Ibomoiye Domor Mienye et al.: Large language models: an overview of foundational architectures, recent trends, and a new taxonomy. In: Discover Applied Sciences. Band 7, Nr. 9, 2. September 2025, ISSN 3004-9261, doi:10.1007/s42452-025-07668-w (englisch, springer.com [abgerufen am 3. April 2026]).
  • Rishi Bommasani et al.: Considerations for governing open foundation models. In: Science. Band 386, Nr. 6718, 11. Oktober 2024, ISSN 0036-8075, S. 151–153, doi:10.1126/science.adp1848 (englisch, science.org [abgerufen am 1. April 2026]).
  • Partha Pratim Ray: ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. In: Internet of Things and Cyber-Physical Systems. Band 3, 2023, S. 121–154, doi:10.1016/j.iotcps.2023.04.003 (englisch, elsevier.com [abgerufen am 28. April 2026]).
  • Guandong Feng et al.: Robust NL-to-Cypher Translation for KBQA: Harnessing Large Language Model with Chain of Prompts. In: Knowledge Graph and Semantic Computing: Knowledge Graph Empowers Artificial General Intelligence. Band 1923. Springer Nature Singapore, Singapore 2023, ISBN 978-981-99-7223-4, S. 317–326, doi:10.1007/978-981-99-7224-1_25 (englisch, springer.com [abgerufen am 8. November 2025]).
  • Yuening Jia: Attention Mechanism in Machine Translation. In: Journal of Physics: Conference Series. Band 1314, Nr. 1, 1. Oktober 2019, ISSN 1742-6588, S. 012186, doi:10.1088/1742-6596/1314/1/012186 (englisch, iop.org [abgerufen am 4. April 2026]).
  • Zhaoyang Niu et al.: A review on the attention mechanism of deep learning. In: Neurocomputing. Band 452, 10. September 2021, ISSN 0925-2312, S. 48–62, doi:10.1016/j.neucom.2021.03.091 (englisch, sciencedirect.com [abgerufen am 4. April 2026]).
  • Rejaul Karim Barbhuiya et al.: Fundamentals of Encoders and Decoders in Generative AI. In: Generative AI: Current Trends and Applications. Band 1177. Springer Nature Singapore, Singapore 2024, ISBN 978-981-97-8459-2, S. 19–33, doi:10.1007/978-981-97-8460-8_2 (englisch, springer.com [abgerufen am 2. April 2026]).
  • Jürgen Schmidhuber: Learning to Control Fast-Weight Memories: An Alternative to Dynamic Recurrent Networks. In: Neural Computation. Band 4, Nr. 1, Januar 1992, ISSN 0899-7667, S. 131–139, doi:10.1162/neco.1992.4.1.131 (englisch, mit.edu [abgerufen am 4. April 2026]).
  • Robert A. Jacobs, Michael I. Jordan, Steven J. Nowlan, Geoffrey E. Hinton: Adaptive Mixtures of Local Experts. In: Neural Computation. Band 3, Nr. 1, Februar 1991, ISSN 0899-7667, S. 79–87, doi:10.1162/neco.1991.3.1.79 (englisch, mit.edu [abgerufen am 3. April 2026]).
  • Philipp Dufter, Martin Schmitt, Hinrich Schütze: Position Information in Transformers: An Overview. In: Computational Linguistics. Band 48, Nr. 3, 1. September 2022, ISSN 0891-2017, S. 733–763, doi:10.1162/coli_a_00445 (englisch, mit.edu [abgerufen am 5. April 2026]).
  • Dhruvin Kotak, Yamini Barge, Tanvi Patel, Nitin Pandya, Rachit Adhvarvyu: Comparison of LLM Models of AI: A Comprehensive Analysis. In: ICT Analysis and Applications. Band 1651. Springer Nature Switzerland, Cham 2026, ISBN 978-3-032-06687-9, S. 93–101, doi:10.1007/978-3-032-06688-6_9 (springer.com [abgerufen am 18. März 2026]).
  • Daya Guo et al.: DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning. In: Nature. Band 645, Nr. 8081, 18. September 2025, ISSN 0028-0836, S. 633–638, doi:10.1038/s41586-025-09422-z, PMID 40962978, PMC 12443585 (freier Volltext) (englisch, nature.com [abgerufen am 3. April 2026]).
  • Shriyank Somvanshi et al.: From Tiny Machine Learning to Tiny Deep Learning: A Survey. In: ACM Computing Surveys. Band 58, Nr. 7, 24. Dezember 2025, ISSN 0360-0300, S. 1–33, doi:10.1145/3776588 (englisch, acm.org [abgerufen am 5. April 2026]).
  • Omar Ghazal et al.: TinyML: Applications, Algorithms, Co-design and Implementations. In: Smart and Connected Health: AI, IoT, and Trustworthy Technologies. Springer Nature Switzerland, Cham 2026, ISBN 978-3-032-06285-7, S. 473–541, doi:10.1007/978-3-032-06286-4_6 (englisch, springer.com [abgerufen am 11. April 2026]).
  • Jasper A. Friedrich: Die Computerspielbranche als Innovationstreiber für technologische und gesellschaftliche Entwicklungen. In: Game-Journalismus. Springer Fachmedien Wiesbaden, Wiesbaden 2023, ISBN 978-3-658-42615-6, S. 163–191, doi:10.1007/978-3-658-42616-3_12 (springer.com [abgerufen am 3. April 2026]).
  • Elizabeth Gibney: Not all ‘open source’ AI models are actually open: here’s a ranking. In: Nature. 19. Juni 2024, ISSN 0028-0836, doi:10.1038/d41586-024-02012-5 (englisch, nature.com [abgerufen am 1. April 2026]).
  • Junnan Li, Dongxu Li, Silvio Savarese, Steven Hoi: BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models. 2023, doi:10.48550/ARXIV.2301.12597, arxiv:2301.12597.
  • Stanley F Chen et al.: Evaluation Metrics For Language Models. 30. Juni 2018, doi:10.1184/R1/6605324.V1 (englisch, cmu.edu [abgerufen am 17. April 2026]).
  • F. Jelinek et al.: Perplexity—a measure of the difficulty of speech recognition tasks. In: The Journal of the Acoustical Society of America. Band 62, S1, 1. Dezember 1977, ISSN 0001-4966, S. S63–S63, doi:10.1121/1.2016299 (englisch, aip.org [abgerufen am 17. April 2026]).
  • Alessio Miaschi et al.: What Makes My Model Perplexed? A Linguistic Investigation on Neural Language Models Perplexity. Association for Computational Linguistics, 2021, S. 40–47, doi:10.18653/v1/2021.deelio-1.5 (englisch, aclweb.org [abgerufen am 17. April 2026]).
  • Ilia Shumailov et al.: AI models collapse when trained on recursively generated data. In: Nature. Band 631, Nr. 8022, 25. Juli 2024, ISSN 0028-0836, S. 755–759, doi:10.1038/s41586-024-07566-y, PMID 39048682, PMC 11269175 (freier Volltext) (englisch, nature.com [abgerufen am 27. Juli 2024]).
  • Adib Bin Rashid et al.: Artificial Intelligence in the Military: An Overview of the Capabilities, Applications, and Challenges. In: International Journal of Intelligent Systems. Band 2023, Nr. 1, Januar 2023, ISSN 0884-8173, doi:10.1155/2023/8676366 (englisch, wiley.com [abgerufen am 22. April 2026]).
  • Junchao Wu, Shu Yang, Runzhe Zhan, Yulin Yuan, Lidia Sam Chao, Derek Fai Wong: A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions. In: Computational Linguistics. Band 51, Nr. 1, 15. März 2025, ISSN 0891-2017, S. 275–338, doi:10.1162/coli_a_00549 (mit.edu [abgerufen am 27. Juni 2026]).

eetimes.com (Global: 4,224th place; German: 5,190th place)

elsevier.com (Global: 365th place; German: 435th place)

linkinghub.elsevier.com

  • Partha Pratim Ray: ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. In: Internet of Things and Cyber-Physical Systems. Band 3, 2023, S. 121–154, doi:10.1016/j.iotcps.2023.04.003 (englisch, elsevier.com [abgerufen am 28. April 2026]).

enclaveai.app (Global: low place; German: low place)

energy.gov (Global: 2,792nd place; German: 4,053rd place)

euronews.com (Global: 587th place; German: 630th place)

federalregister.gov (Global: 2,513th place; German: 4,413th place)

forbes.com (Global: 71st place; German: 140th place)

fraunhofer.de (Global: 7,521st place; German: 787th place)

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github.com (Global: 380th place; German: 255th place)

global.toyota (Global: 3,688th place; German: low place)

huggingface.co (Global: low place; German: low place)

iaea.org (Global: 1,135th place; German: 581st place)

ibm.com (Global: 1,369th place; German: 1,458th place)

idsia.ch (Global: low place; German: low place)

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insidegovernmentcontracts.com (Global: low place; German: low place)

  • Nooree Lee, Stephanie Barna, Robert Huffman, Ryan Burnette, Krissy Chapman, Eunsun Cho: Pentagon Releases Artificial Intelligence Strategy. In: Inside Government Contracts. Covington & Burling LLP, 3. Februar 2026, abgerufen am 1. April 2026 (amerikanisches Englisch).

iop.org (Global: 1,046th place; German: 673rd place)

iopscience.iop.org

jalammar.github.io (Global: low place; German: low place)

kad8.com (Global: low place; German: low place)

llm-book.com (Global: low place; German: low place)

  • Jay Alammar, Maarten Grootendorst: Hands-On Large Language Models: Language Understanding and Generation. O’Reilly Media, Sebastopol, CA 2024, ISBN 978-1-0981-5096-9 (llm-book.com [abgerufen am 3. April 2026]).

llm-stats.com (Global: low place; German: low place)

mckinsey.com (Global: 8,567th place; German: 7,447th place)

microsoft.com (Global: 263rd place; German: 323rd place)

military.com (Global: 2,449th place; German: 2,848th place)

mit.edu (Global: 476th place; German: 920th place)

direct.mit.edu

  • Jürgen Schmidhuber: Learning to Control Fast-Weight Memories: An Alternative to Dynamic Recurrent Networks. In: Neural Computation. Band 4, Nr. 1, Januar 1992, ISSN 0899-7667, S. 131–139, doi:10.1162/neco.1992.4.1.131 (englisch, mit.edu [abgerufen am 4. April 2026]).
  • Robert A. Jacobs, Michael I. Jordan, Steven J. Nowlan, Geoffrey E. Hinton: Adaptive Mixtures of Local Experts. In: Neural Computation. Band 3, Nr. 1, Februar 1991, ISSN 0899-7667, S. 79–87, doi:10.1162/neco.1991.3.1.79 (englisch, mit.edu [abgerufen am 3. April 2026]).
  • Philipp Dufter, Martin Schmitt, Hinrich Schütze: Position Information in Transformers: An Overview. In: Computational Linguistics. Band 48, Nr. 3, 1. September 2022, ISSN 0891-2017, S. 733–763, doi:10.1162/coli_a_00445 (englisch, mit.edu [abgerufen am 5. April 2026]).
  • Junchao Wu, Shu Yang, Runzhe Zhan, Yulin Yuan, Lidia Sam Chao, Derek Fai Wong: A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions. In: Computational Linguistics. Band 51, Nr. 1, 15. März 2025, ISSN 0891-2017, S. 275–338, doi:10.1162/coli_a_00549 (mit.edu [abgerufen am 27. Juni 2026]).

ml.energy (Global: low place; German: low place)

  • The ML.ENERGY Leaderboard. In: ML.ENERGY. 2026, abgerufen am 11. April 2026 (englisch).
  • Zeus. In: ML.ENERGY. 2026, abgerufen am 11. April 2026 (englisch).

mlcommons.org (Global: low place; German: low place)

nature.com (Global: 207th place; German: 227th place)

nih.gov (Global: 5th place; German: 7th place)

ncbi.nlm.nih.gov

ntia.gov (Global: low place; German: low place)

nvidia.com (Global: 2,958th place; German: 3,177th place)

blogs.nvidia.com

developer.nvidia.com

nvidia.com

  • NVIDIA H200 GPU. In: Nvidia. 2026, abgerufen am 20. April 2026 (amerikanisches Englisch).

nxp.com (Global: low place; German: low place)

nytimes.com (Global: 7th place; German: 15th place)

  • Sheera Frenkel et al.: Mutually Automated Destruction: The Escalating Global A.I. Arms Race. In: The New York Times. 12. April 2026, ISSN 0362-4331 (englisch, nytimes.com [abgerufen am 22. April 2026]).
  • Kevin Roose: Anthropic Claims Its New A.I. Model, Mythos, Is a Cybersecurity ‘Reckoning’. In: The New York Times. 7. April 2026, ISSN 0362-4331 (englisch, nytimes.com [abgerufen am 12. April 2026]).

nzz.ch (Global: 710th place; German: 40th place)

ongraph.com (Global: low place; German: low place)

openai.com (Global: 4,607th place; German: 3,525th place)

openai.com

cdn.openai.com

  • Alec Radford et al.: Improving Language Understanding by Generative Pre-Training. Hrsg.: OpenAI. 2018 (englisch, openai.com [PDF]).
  • Alec Radford et al.: Language Models are Unsupervised Multitask Learners. Hrsg.: OpenAI. San Francisco, CA 2019 (englisch, openai.com [PDF]).

help.openai.com

developers.openai.com

opensource.org (Global: low place; German: low place)

ourworldindata.org (Global: 2,491st place; German: 1,929th place)

pbs.org (Global: 260th place; German: 801st place)

redirecter.toolforge.org (Global: 29th place; German: 2nd place)

research.google (Global: low place; German: low place)

  • Transformer: A Novel Neural Network Architecture for Language Understanding. In: Google Research. 31. August 2017, abgerufen am 3. April 2026 (englisch).
    1. The sequential nature of RNNs also makes it more difficult to fully take advantage of modern fast computing devices such as TPUs and GPUs, which excel at parallel and not sequential processing. Convolutional neural networks (CNNs) are much less sequential than RNNs, but in CNN architectures like ByteNet or ConvS2S the number of steps required to combine information from distant parts of the input still grows with increasing distance.

reuters.com (Global: 38th place; German: 126th place)

science.org (Global: 1,007th place; German: 1,329th place)

sciencedirect.com (Global: 137th place; German: 321st place)

simonwillison.net (Global: low place; German: low place)

springer.com (Global: 182nd place; German: 148th place)

link.springer.com

  • Ibomoiye Domor Mienye et al.: Large language models: an overview of foundational architectures, recent trends, and a new taxonomy. In: Discover Applied Sciences. Band 7, Nr. 9, 2. September 2025, ISSN 3004-9261, doi:10.1007/s42452-025-07668-w (englisch, springer.com [abgerufen am 3. April 2026]).
  • Guandong Feng et al.: Robust NL-to-Cypher Translation for KBQA: Harnessing Large Language Model with Chain of Prompts. In: Knowledge Graph and Semantic Computing: Knowledge Graph Empowers Artificial General Intelligence. Band 1923. Springer Nature Singapore, Singapore 2023, ISBN 978-981-99-7223-4, S. 317–326, doi:10.1007/978-981-99-7224-1_25 (englisch, springer.com [abgerufen am 8. November 2025]).
  • Rejaul Karim Barbhuiya et al.: Fundamentals of Encoders and Decoders in Generative AI. In: Generative AI: Current Trends and Applications. Band 1177. Springer Nature Singapore, Singapore 2024, ISBN 978-981-97-8459-2, S. 19–33, doi:10.1007/978-981-97-8460-8_2 (englisch, springer.com [abgerufen am 2. April 2026]).
  • Dhruvin Kotak, Yamini Barge, Tanvi Patel, Nitin Pandya, Rachit Adhvarvyu: Comparison of LLM Models of AI: A Comprehensive Analysis. In: ICT Analysis and Applications. Band 1651. Springer Nature Switzerland, Cham 2026, ISBN 978-3-032-06687-9, S. 93–101, doi:10.1007/978-3-032-06688-6_9 (springer.com [abgerufen am 18. März 2026]).
  • Omar Ghazal et al.: TinyML: Applications, Algorithms, Co-design and Implementations. In: Smart and Connected Health: AI, IoT, and Trustworthy Technologies. Springer Nature Switzerland, Cham 2026, ISBN 978-3-032-06285-7, S. 473–541, doi:10.1007/978-3-032-06286-4_6 (englisch, springer.com [abgerufen am 11. April 2026]).
  • Jasper A. Friedrich: Die Computerspielbranche als Innovationstreiber für technologische und gesellschaftliche Entwicklungen. In: Game-Journalismus. Springer Fachmedien Wiesbaden, Wiesbaden 2023, ISBN 978-3-658-42615-6, S. 163–191, doi:10.1007/978-3-658-42616-3_12 (springer.com [abgerufen am 3. April 2026]).

stephenwolfram.com (Global: low place; German: low place)

writings.stephenwolfram.com

  • Stephen Wolfram: What Is ChatGPT Doing … and Why Does It Work? In: Stephen Wolfram Writings. 14. Februar 2023 (englisch, stephenwolfram.com [abgerufen am 11. April 2026]).

t3n.de (Global: low place; German: 1,215th place)

tagesschau.de (Global: 772nd place; German: 42nd place)

technologyreview.com (Global: 2,515th place; German: 3,350th place)

theguardian.com (Global: 16th place; German: 22nd place)

  • Richard Lea: Google swallows 11,000 novels to improve AI's conversation. In: The Guardian. 28. September 2016, ISSN 0261-3077 (theguardian.com [abgerufen am 2. April 2026]).

theregister.com (Global: 2,921st place; German: 4,356th place)

  • Tobias Mann: How to run an LLM locally on your PC in less than 10 minutes. In: The Register. 17. März 2024 (theregister.com [abgerufen am 11. April 2026]).

time.com (Global: 84th place; German: 206th place)

toloka.ai (Global: low place; German: low place)

war.gov (Global: 4,436th place; German: 8,442nd place)

web.archive.org (Global: 1st place; German: 1st place)

wiley.com (Global: 150th place; German: 246th place)

onlinelibrary.wiley.com

  • Adib Bin Rashid et al.: Artificial Intelligence in the Military: An Overview of the Capabilities, Applications, and Challenges. In: International Journal of Intelligent Systems. Band 2023, Nr. 1, Januar 2023, ISSN 0884-8173, doi:10.1155/2023/8676366 (englisch, wiley.com [abgerufen am 22. April 2026]).

x.ai (Global: low place; German: low place)

zdb-katalog.de (Global: 107th place; German: 5th place)

  • Ibomoiye Domor Mienye et al.: Large language models: an overview of foundational architectures, recent trends, and a new taxonomy. In: Discover Applied Sciences. Band 7, Nr. 9, 2. September 2025, ISSN 3004-9261, doi:10.1007/s42452-025-07668-w (englisch, springer.com [abgerufen am 3. April 2026]).
  • Rishi Bommasani et al.: Considerations for governing open foundation models. In: Science. Band 386, Nr. 6718, 11. Oktober 2024, ISSN 0036-8075, S. 151–153, doi:10.1126/science.adp1848 (englisch, science.org [abgerufen am 1. April 2026]).
  • Yuening Jia: Attention Mechanism in Machine Translation. In: Journal of Physics: Conference Series. Band 1314, Nr. 1, 1. Oktober 2019, ISSN 1742-6588, S. 012186, doi:10.1088/1742-6596/1314/1/012186 (englisch, iop.org [abgerufen am 4. April 2026]).
  • Zhaoyang Niu et al.: A review on the attention mechanism of deep learning. In: Neurocomputing. Band 452, 10. September 2021, ISSN 0925-2312, S. 48–62, doi:10.1016/j.neucom.2021.03.091 (englisch, sciencedirect.com [abgerufen am 4. April 2026]).
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zeit.de (Global: 301st place; German: 14th place)

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