Large language model (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Large language model" in English language version.

Last modified: 09:19:39, 20 September 2026 (UTC)

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aclanthology.org (Global: low place; English: 8,900^th place)

Rogers, Anna; Kovaleva, Olga; Rumshisky, Anna (2020). "A Primer in BERTology: What We Know About How BERT Works". Transactions of the Association for Computational Linguistics. 8: 842–866. arXiv:2002.12327. doi:10.1162/tacl_a_00349. S2CID 211532403. Archived from the original on 3 April 2022. Retrieved 21 January 2024.
Movva, Rajiv; Balachandar, Sidhika; Peng, Kenny; Agostini, Gabriel; Garg, Nikhil; Pierson, Emma (2024). "Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers". Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). pp. 1223–1243. arXiv:2307.10700. doi:10.18653/v1/2024.naacl-long.67. Retrieved 8 December 2024.
Kaushal, Ayush; Mahowald, Kyle (6 June 2022). "What do tokens know about their characters and how do they know it?" (PDF). NAACL.
Dodge, Jesse; Sap, Maarten; Marasović, Ana; Agnew, William; Ilharco, Gabriel; Groeneveld, Dirk; et al. (2021). "Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus" (PDF). Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. pp. 1286–1305. arXiv:2104.08758. doi:10.18653/v1/2021.emnlp-main.98.
Lee, Katherine; Ippolito, Daphne; Nystrom, Andrew; Zhang, Chiyuan; Eck, Douglas; Callison-Burch, Chris; et al. (May 2022). "Deduplicating Training Data Makes Language Models Better" (PDF). Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). pp. 8424–8445. doi:10.18653/v1/2022.acl-long.577.
Peng, Bo; Alcaide, Eric; Anthony, Quentin; Albalak, Alon; Arcadinho, Samuel; Biderman, Stella; et al. (2023). "RWKV: Reinventing RNNS for the Transformer Era". EMNLP: 14048–14077. arXiv:2305.13048. doi:10.18653/v1/2023.findings-emnlp.936.
Wang, Yizhong; Kordi, Yeganeh; Mishra, Swaroop; Liu, Alisa; Smith, Noah A.; Khashabi, Daniel; et al. (2023). "Self-Instruct: Aligning Language Models with Self-Generated Instructions". Self-Instruct: Aligning Language Model with Self Generated Instructions. pp. 13484–13508. doi:10.18653/v1/2023.acl-long.754.
Hao, Shibo; Gu, Yi; Ma, Haodi; Jiahua Hong, Joshua; Wang, Zhen; Zhe Wang, Daisy; et al. (1 May 2023). "Reasoning with Language Model is Planning with World Model". EMNLP: 8154–8173. doi:10.18653/v1/2023.emnlp-main.507.
Pilehvar, Mohammad Taher; Camacho-Collados, Jose (June 2019). "Proceedings of the 2019 Conference of the North". Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers). Minneapolis, Minnesota: Association for Computational Linguistics: 1267–1273. doi:10.18653/v1/N19-1128. S2CID 102353817. Archived from the original on 27 June 2023. Retrieved 27 June 2023.
Nangia, Nikita; Vania, Clara; Bhalerao, Rasika; Bowman, Samuel R. (November 2020). "CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models". In Webber, Bonnie; Cohn, Trevor; He, Yulan; Liu, Yang (eds.). Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP). Association for Computational Linguistics. pp. 1953–1967. arXiv:2010.00133. doi:10.18653/v1/2020.emnlp-main.154.
Nadeem, Moin; Bethke, Anna; Reddy, Siva (August 2021). "StereoSet: Measuring stereotypical bias in pretrained language models". In Zong, Chengqing; Xia, Fei; Li, Wenjie; Navigli, Roberto (eds.). Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics. pp. 5356–5371. arXiv:2004.09456. doi:10.18653/v1/2021.acl-long.416.
Clark, Christopher; Lee, Kenton; Chang, Ming-Wei; Kwiatkowski, Tom; Collins, Michael; Toutanova, Kristina (2019). "BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions". ACL: 2924–2936. doi:10.18653/v1/N19-1300.
Niven, Timothy; Kao, Hung-Yu (2019). "Probing Neural Network Comprehension of Natural Language Arguments". ACL: 4658–4664. doi:10.18653/v1/P19-1459.

acm.org (Global: 1,200^th place; English: 821^st place)

dl.acm.org

Sutskever, Ilya; Vinyals, Oriol; Le, Quoc V. (2014). "Sequence to sequence learning with neural networks". Proceedings of the 28th International Conference on Neural Information Processing Systems. 2: 3104–3112.
Lin, Zhenghao; Gou, Zhibin; Gong, Yeyun; Liu, Xiao; Shen, Yelong; Xu, Ruochen; et al. (11 April 2024). "Rho-1: Not All Tokens Are What You Need". NeurIPS. 37: 29029–29063. ISBN 979-8-3313-1438-5.{{cite journal}}: CS1 maint: periodical has ISBN (link)
Dettmers, Tim; Pagnoni, Artidoro; Holtzman, Ari; Zettlemoyer, Luke (10 December 2023). "QLORA: efficient finetuning of quantized LLMs". NeurIPS: 10088–10115.
Wang, Zihao; Cai, Shaofei; Liu, Anji; Ma, Xiaojian; Liang, Yitao (3 February 2023). "Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents". NeurIPS: 34153–34189.
Shinn, Noah; Cassano, Federico; Labash, Beck; Gopinath, Ashwin; Narasimhan, Karthik; Yao, Shunyu (1 March 2023). "Reflexion: Language Agents with Verbal Reinforcement Learning". NeurIPS: 34153–34189.
Wu, Tongshuang; Jiang, Ellen; Donsbach, Aaron; Gray, Jeff; Molina, Alejandra; Terry, Michael; et al. (13 March 2022). PromptChainer: Chaining Large Language Model Prompts through Visual Programming. CHI Conference on Human Factors in Computing Systems. arXiv:2203.06566. doi:10.1145/3491101.3519729.
Wei, Jason; Wang, Xuezhi; Schuurmans, Dale; Bosma, Maarten; Ichter, Brian; Xia, Fei; et al. (10 January 2023). "Chain-of-Thought Prompting Elicits Reasoning in Large Language Models". NeurIPS: 24824–24837. ISBN 978-1-7138-7108-8.{{cite journal}}: CS1 maint: periodical has ISBN (link)
Driess, Danny; Xia, Fei; Sajjadi, Mehdi S. M.; Lynch, Corey; Chowdhery, Aakanksha; Ichter, Brian; et al. (1 March 2023). "PaLM-E: An Embodied Multimodal Language Model". ICML. 202: 8469–8488.
Li, Junnan; Li, Dongxu; Savarese, Silvio; Hoi, Steven (1 January 2023). "BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models". ICML. 202: 19730–19742.
Hoffmann, Jordan; Borgeaud, Sebastian; Mensch, Arthur; Buchatskaya, Elena; Cai, Trevor; Rutherford, Eliza; et al. (29 March 2022). "Training Compute-Optimal Large Language Models". NeurIPS: 30016–30030. ISBN 978-1-7138-7108-8.{{cite journal}}: CS1 maint: periodical has ISBN (link)
Ji, Ziwei; Lee, Nayeon; Frieske, Rita; Yu, Tiezheng; Su, Dan; Xu, Yan; et al. (November 2022). "Survey of Hallucination in Natural Language Generation" (pdf). ACM Computing Surveys. 55 (12). Association for Computing Machinery: 1–38. arXiv:2202.03629. doi:10.1145/3571730. S2CID 246652372. Archived from the original on 26 March 2023. Retrieved 15 January 2023.
Kotek, Hadas; Dockum, Rikker; Sun, David (5 November 2023). "Gender bias and stereotypes in Large Language Models". Proceedings of the ACM Collective Intelligence Conference. New York, NY, USA: Association for Computing Machinery. pp. 12–24. arXiv:2308.14921. doi:10.1145/3582269.3615599. ISBN 979-8-4007-0113-9.
Greshake, Kai; Abdelnabi, Sahar; Mishra, Shailesh; Endres, Christoph; Holz, Thorsten; Fritz, Mario (1 February 2023). "Not What You've Signed Up For: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection". Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security. pp. 79–90. doi:10.1145/3605764.3623985. ISBN 979-8-4007-0260-0.

cacm.acm.org

Luo, Queenie; Puett, Michael J.; Smith, Michael D. (22 July 2024). "A Perspectival Mirror of the Elephant". Communications of the ACM. 67 (8): 98–105. doi:10.1145/3670241.

adasci.org (Global: low place; English: low place)

Mehta, Sourabh (3 July 2024). "How Much Energy Do LLMs Consume? Unveiling the Power Behind AI". Association of Data Scientists. Retrieved 27 January 2025.

adsabs.harvard.edu (Global: 14^th place; English: 9^th place)

ui.adsabs.harvard.edu

Chen, Leiyu; Li, Shaobo; Bai, Qiang; Yang, Jing; Jiang, Sanlong; Miao, Yanming (2021). "Review of Image Classification Algorithms Based on Convolutional Neural Networks". Remote Sensing. 13 (22): 4712. Bibcode:2021RemS...13.4712C. doi:10.3390/rs13224712.
Yu, Shaoyun; Gu, Chanyuan; Huang, Kexin; Li, Ping (23 May 2024). "Predicting the next sentence (not word) in large language models: What model-brain alignment tells us about discourse comprehension". Science. 10 (21) eadn7744. Bibcode:2024SciA...10N7744Y. doi:10.1126/sciadv.adn7744. PMC 11114233. PMID 38781343.
Gibney, Elizabeth (30 January 2025). "China's cheap, open AI model DeepSeek thrills scientists". Nature. 638 (8049): 13–14. Bibcode:2025Natur.638...13G. doi:10.1038/d41586-025-00229-6. PMID 39849139. Retrieved 3 February 2025.
Kumar, Puneet; Khokher, Vedanti; Gupta, Yukti; Raman, Balasubramanian (2021). Hybrid Fusion Based Approach for Multimodal Emotion Recognition with Insufficient Labeled Data. pp. 314–318. Bibcode:2021icip.conf...74K. doi:10.1109/ICIP42928.2021.9506714. ISBN 978-1-6654-4115-5.
Lin, Zeming; Akin, Halil; Rao, Roshan; Hie, Brian; Zhu, Zhongkai; Lu, Wenting; et al. (17 March 2023). "Evolutionary-scale prediction of atomic-level protein structure with a language model". Science. 379 (6637): 1123–1130. Bibcode:2023Sci...379.1123L. bioRxiv 10.1101/2022.07.20.500902. doi:10.1126/science.ade2574. PMID 36927031.
Hayes, Thomas; Rao, Roshan; Akin, Halil; Sofroniew, Nicholas J.; Oktay, Deniz; Lin, Zeming; et al. (21 February 2025). "Simulating 500 million years of evolution with a language model". Science. 387 (6736): 850–858. Bibcode:2025Sci...387..850H. doi:10.1126/science.ads0018. PMID 39818825.
Mitchell, Melanie; Krakauer, David C. (28 March 2023). "The debate over understanding in AI's large language models". Proceedings of the National Academy of Sciences. 120 (13) e2215907120. arXiv:2210.13966. Bibcode:2023PNAS..12015907M. doi:10.1073/pnas.2215907120. PMC 10068812. PMID 36943882.
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Bermejo, Vicente J.; Gago, Andrés; Gálvez, Ramiro H.; Harari, Nicolás (2025). "LLMs outperform outsourced human coders on complex textual analysis". Scientific Reports. 15 (1) 40122. Nature Portfolio. Bibcode:2025NatSR..1540122B. doi:10.1038/s41598-025-23798-y. PMC 12623721. PMID 41249236.
Gilardi, Fabrizio; Alizadeh, Meysam; Kubli, Maël (2023). "ChatGPT outperforms crowd workers for text-annotation tasks". Proceedings of the National Academy of Sciences of the United States of America. 120 (30) e2305016120. National Academy of Sciences. arXiv:2303.15056. Bibcode:2023PNAS..12005016G. doi:10.1073/pnas.2305016120. PMC 10372638. PMID 37463210.
Hofmann, Valentin; Kalluri, Pratyusha Ria; Jurafsky, Dan; King, Sharese (5 September 2024). "AI generates covertly racist decisions about people based on their dialect". Nature. 633 (8028): 147–154. Bibcode:2024Natur.633..147H. doi:10.1038/s41586-024-07856-5. ISSN 0028-0836. PMC 11374696. PMID 39198640.

apa.org (Global: 1,327^th place; English: 1,093^rd place)

doi.apa.org

Rousmaniere, Tony; Zhang, Yimeng; Li, Xu; Shah, Siddharth (21 July 2025). "Large language models as mental health resources: Patterns of use in the United States". Practice Innovations. 11 (2): 139–155. doi:10.1037/pri0000292. ISSN 2377-8903.

arstechnica.com (Global: 473^rd place; English: 338^th place)

Edwards, Benj (9 May 2023). "AI gains "values" with Anthropic's new Constitutional AI chatbot approach". Ars Technica. Retrieved 30 June 2025.
Edwards, Benj (28 September 2023). "AI language models can exceed PNG and FLAC in lossless compression, says study". Ars Technica. Retrieved 29 May 2025.
Edwards, Benj (15 January 2024). "AI poisoning could turn models into destructive "sleeper agents," says Anthropic". Ars Technica. Retrieved 19 July 2025.
Edwards, Benj (26 March 2025). "Open source devs say AI crawlers dominate traffic, forcing blocks on entire countries". Ars Technica. Retrieved 31 December 2025.
Belanger, Ashley (29 January 2025). "AI haters build tarpits to trap and trick AI scrapers that ignore robots.txt". Ars Technica. Retrieved 31 December 2025.

arxiv.org (Global: 49^th place; English: 31^st place)

Brown, Tom B.; Mann, Benjamin; Ryder, Nick; Subbiah, Melanie; Kaplan, Jared; Dhariwal, Prafulla; et al. (December 2020). Larochelle, H.; Ranzato, M.; Hadsell, R.; Balcan, M.F.; Lin, H. (eds.). "Language Models are Few-Shot Learners" (PDF). Advances in Neural Information Processing Systems. 33. Curran Associates, Inc.: 1877–1901. arXiv:2005.14165. Archived (PDF) from the original on 17 November 2023. Retrieved 14 March 2023.
Zhao, Wayne Xin; Zhou, Kun; Li, Junyi; Tang, Tianyi; Dong, Zican; Hou, Yupeng; et al. (December 2026). "A Survey of Large Language Models". Frontiers of Computer Science. 20 (12) 2012627. arXiv:2303.18223. doi:10.1007/s11704-026-60308-3. Typically, large language models (LLMs) refer to Transformer language models that contain hundreds of billions (or more) of parameters
Goodman, Joshua (9 August 2001). "A Bit of Progress in Language Modeling". Computer Speech & Language. 15 (4): 403–434. arXiv:cs/0108005. doi:10.1006/csla.2001.0174.
Bahdanau, Dzmitry; Cho, Kyunghyun; Bengio, Yoshua (2014). "Neural Machine Translation by Jointly Learning to Align and Translate". arXiv:1409.0473 [cs.CL].
Rogers, Anna; Kovaleva, Olga; Rumshisky, Anna (2020). "A Primer in BERTology: What We Know About How BERT Works". Transactions of the Association for Computational Linguistics. 8: 842–866. arXiv:2002.12327. doi:10.1162/tacl_a_00349. S2CID 211532403. Archived from the original on 3 April 2022. Retrieved 21 January 2024.
Movva, Rajiv; Balachandar, Sidhika; Peng, Kenny; Agostini, Gabriel; Garg, Nikhil; Pierson, Emma (2024). "Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers". Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). pp. 1223–1243. arXiv:2307.10700. doi:10.18653/v1/2024.naacl-long.67. Retrieved 8 December 2024.
Dodge, Jesse; Sap, Maarten; Marasović, Ana; Agnew, William; Ilharco, Gabriel; Groeneveld, Dirk; et al. (2021). "Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus" (PDF). Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. pp. 1286–1305. arXiv:2104.08758. doi:10.18653/v1/2021.emnlp-main.98.
Peng, Bo; Alcaide, Eric; Anthony, Quentin; Albalak, Alon; Arcadinho, Samuel; Biderman, Stella; et al. (2023). "RWKV: Reinventing RNNS for the Transformer Era". EMNLP: 14048–14077. arXiv:2305.13048. doi:10.18653/v1/2023.findings-emnlp.936.
Zaib, Munazza; Sheng, Quan Z.; Zhang, Wei Emma (4 February 2020). "A Short Survey of Pre-trained Language Models for Conversational AI-A New Age in NLP". Proceedings of the Australasian Computer Science Week Multiconference. pp. 1–4. arXiv:2104.10810. doi:10.1145/3373017.3373028. ISBN 978-1-4503-7697-6. S2CID 211040895.
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Lewis, Patrick; Perez, Ethan; Piktus, Aleksandra; Petroni, Fabio; Karpukhin, Vladimir; Goyal, Naman; et al. (2020). "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks". Advances in Neural Information Processing Systems. 33. Curran Associates, Inc.: 9459–9474. arXiv:2005.11401. Archived from the original on 12 June 2023. Retrieved 12 June 2023.
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Wu, Tongshuang; Jiang, Ellen; Donsbach, Aaron; Gray, Jeff; Molina, Alejandra; Terry, Michael; et al. (13 March 2022). PromptChainer: Chaining Large Language Model Prompts through Visual Programming. CHI Conference on Human Factors in Computing Systems. arXiv:2203.06566. doi:10.1145/3491101.3519729.
Zhang, Hang; Li, Xin; Bing, Lidong (1 June 2023). "Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding". EMNLP. arXiv:2306.02858.
Alayrac, Jean-Baptiste; Donahue, Jeff; Luc, Pauline; Miech, Antoine; Barr, Iain; Hasson, Yana; et al. (6 December 2022). "Flamingo: a Visual Language Model for Few-Shot Learning". Advances in Neural Information Processing Systems. 35 (12): 23716–23736. arXiv:2204.14198. doi:10.1093/nsr/nwae403. PMC 11645129. PMID 39679213. Archived from the original on 2 July 2023. Retrieved 2 July 2023.
Caballero, Ethan; Gupta, Kshitij; Rish, Irina; Krueger, David (2022). "Broken Neural Scaling Laws". arXiv:2210.14891 [cs.LG].
Schaeffer, Rylan; Miranda, Brando; Koyejo, Sanmi (1 April 2023). "Are Emergent Abilities of Large Language Models a Mirage?". NeurIPS. arXiv:2304.15004.
Nanda, Neel; Chan, Lawrence; Lieberum, Tom; Smith, Jess; Steinhardt, Jacob (1 January 2023). "Progress measures for grokking via mechanistic interpretability". arXiv:2301.05217 [cs.LG].
Mitchell, Melanie; Krakauer, David C. (28 March 2023). "The debate over understanding in AI's large language models". Proceedings of the National Academy of Sciences. 120 (13) e2215907120. arXiv:2210.13966. Bibcode:2023PNAS..12015907M. doi:10.1073/pnas.2215907120. PMC 10068812. PMID 36943882.
Bubeck, Sébastien; Chandrasekaran, Varun; Eldan, Ronen; Gehrke, Johannes; Horvitz, Eric; Kamar, Ece; et al. (2023). "Machine culture". Nature Human Behaviour. 7 (11): 1855–1868. arXiv:2303.12712. doi:10.1038/s41562-023-01742-2. PMID 37985914.
Ji, Ziwei; Lee, Nayeon; Frieske, Rita; Yu, Tiezheng; Su, Dan; Xu, Yan; et al. (November 2022). "Survey of Hallucination in Natural Language Generation" (pdf). ACM Computing Surveys. 55 (12). Association for Computing Machinery: 1–38. arXiv:2202.03629. doi:10.1145/3571730. S2CID 246652372. Archived from the original on 26 March 2023. Retrieved 15 January 2023.
Varshney, Neeraj; Yao, Wenlin; Zhang, Hongming; Chen, Jianshu; Yu, Dong (2023). "A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation". arXiv:2307.03987 [cs.CL].
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Large language model (English Wikipedia)

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