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Paper Citation Record · LEDGER

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2501.11496.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.11496 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:15:44.845066Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:44:49.109466Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-15T20:44:49.239486Z

Reference resolution

34 of 34 outbound references displayed

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External citation measurements

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Outbound references

Observation 5eec42d8-621d-4c0d-a9fb-7ca0f28784c7 · outbound

This paper cites (2025) Language diversity index.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges (2025) Language diversity index

Reference 1

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Observation 63d9ecbf-bebe-4277-8238-c8cd2b3972a9 · outbound

This paper cites Global predictors of language endangerment and the future of linguistic diversity,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Global predictors of language endangerment and the future of linguistic diversity,

Reference 2

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This paper cites Recommendation concerning the promotion and use of multilingualism and universal access to cyberspace,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Recommendation concerning the promotion and use of multilingualism and universal access to cyberspace,

Reference 3

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Observation 04e95e24-98cc-49fe-bf54-2da07ff64ba6 · outbound

This paper cites Generative ai as digital media,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Generative ai as digital media,

Reference 4

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Observation 92c956a8-be9c-4511-9197-02e6b858eb06 · outbound

This paper cites Multimodal generative ai for african language preserva- tion: A framework for language documentation and revitalization,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Multimodal generative ai for african language preserva- tion: A framework for language documentation and revitalization,

Reference 5

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This paper cites Framework for fairness in machine learning using detecting and mitigating bias in ai algorithms,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Framework for fairness in machine learning using detecting and mitigating bias in ai algorithms,

Reference 6

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Source-reported events for the cited work

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Observation 17f60055-c111-4265-a7de-62b64705fa2a · outbound

This paper cites Attention is all you need,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Attention is all you need,

Reference 7

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This paper cites Recent advances in generative ai and large language models: Current status, challenges, and perspec- tives,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Recent advances in generative ai and large language models: Current status, challenges, and perspec- tives,

Reference 8

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This paper cites Schillaci, LLM Adoption Trends and Associated Risks.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Schillaci, LLM Adoption Trends and Associated Risks

Reference 9

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This paper cites Ai-driven territorial intelligence: An integrated approach to enhancing digital sovereignty,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Ai-driven territorial intelligence: An integrated approach to enhancing digital sovereignty,

Reference 10

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Observation cb4fbd0e-84c6-4947-b699-df767c10dd9d · outbound

This paper cites Peter-lucas jones: Using ai to preserve indigenous languages,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Peter-lucas jones: Using ai to preserve indigenous languages,

Reference 11

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This paper cites When large language models meet personalization: perspectives of challenges and opportunities,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges When large language models meet personalization: perspectives of challenges and opportunities,

Reference 12

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This paper cites Privacy-preserving techniques in generative ai and large language models: A narrative review,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Privacy-preserving techniques in generative ai and large language models: A narrative review,

Reference 13

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This paper cites Large language models: A comprehensive survey of its applications, challenges, limitations, and future prospects,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Large language models: A comprehensive survey of its applications, challenges, limitations, and future prospects,

Reference 14

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This paper cites Language preservation efforts get an ai boost,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Language preservation efforts get an ai boost,

Reference 15

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This paper cites Impact of conversational and generative ai systems on libraries: A use case large language model (llm),.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Impact of conversational and generative ai systems on libraries: A use case large language model (llm),

Reference 16

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Toward text data augmentation for sentiment analysis,

Reference 17

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This paper cites Adapting multilingual LLMs to low-resource languages with knowledge graphs via adapters,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Adapting multilingual LLMs to low-resource languages with knowledge graphs via adapters,

Reference 18

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Exploration of tpus for ai applications,

Reference 19

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Here’s what the sellside is saying about deepseek,

Reference 20

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges The national science foundation launches nairr pilot to democratize ai research,

Reference 21

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Does the grammatical structure of prompts influence the responses of generative artificial intelligence? an exploratory analysis in spanish,

Reference 22

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Complexities for non-latin languages & llm evaluations,

Reference 23

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This paper cites The challenge of ai-generated content in scientific publishing,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges The challenge of ai-generated content in scientific publishing,

Reference 24

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges AI-based Framework for Discriminating Human-authored and AI- generated Text,

Reference 25

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Artificial intelligence may affect diversity: architecture and cultural context reflected through chatgpt, midjourney, and google maps,

Reference 26

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This paper cites Ai, cultural heritage, and bias: Some key queries that arise from the use of genai,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Ai, cultural heritage, and bias: Some key queries that arise from the use of genai,

Reference 27

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges The geopolitics of open source ai,

Reference 28

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This paper cites Available: https://www.mdpi.com/2571-9408/7/11/287.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Available: https://www.mdpi.com/2571-9408/7/11/287

Reference 29

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges (2025) Technology foundations of generative ai: Architectures, algorithms, and innovations

Reference 30

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Future shock: Generative ai and the international ai policy and governance crisis,

Reference 31

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Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Ai for impacts: A framework for evaluating ai interventions in language preservation,

Reference 32

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This paper cites Following generative ai down the rabbit hole: Redefining copyright’s boundaries in the age of human-machine collaborations,.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Following generative ai down the rabbit hole: Redefining copyright’s boundaries in the age of human-machine collaborations,

Reference 33

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Observation 50b14cf7-044d-43ff-ab49-b471c73a7afe · outbound

This paper cites Available: https://www.mdpi.com/2078-2489/15/11/697.

Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges Available: https://www.mdpi.com/2078-2489/15/11/697

Reference 2024

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:15:45.610609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Pith citing papers

Observation de949d48-5437-433d-81bc-bc3a912d0dae · inbound

Tiny QA Benchmark++: Ultra-Lightweight, Synthetic Multilingual Dataset Generation & Smoke-Tests for Continuous LLM Evaluation cites this paper.

Tiny QA Benchmark++: Ultra-Lightweight, Synthetic Multilingual Dataset Generation & Smoke-Tests for Continuous LLM Evaluation Generative AI and Large Language Models in Language Preservation: Opportunities and Challenges

Reference 7

Resolution
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local_arxiv, observed 2026-08-15T20:44:49.244691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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