Towards Responsible Governing AI Proliferation | Paper Citation Record

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This paper cites The Making of the Atomic Bomb.

Towards Responsible Governing AI Proliferation The Making of the Atomic Bomb

Reference 1

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This paper cites The vulnerable world hypothesis.

Towards Responsible Governing AI Proliferation The vulnerable world hypothesis

Reference 2

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This paper cites Compute trends across three eras of machine learn- ing.

Towards Responsible Governing AI Proliferation Compute trends across three eras of machine learn- ing

Reference 3

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This paper cites Computing Power and the Governance of Artificial Intelligence.

Towards Responsible Governing AI Proliferation Computing Power and the Governance of Artificial Intelligence

Reference 4

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Observation dd5a33f7-ce9d-451a-822b-5c8511c5a1fa · outbound

This paper cites Frontier AI Regulation: Managing Emerging Risks to Public Safety.

Towards Responsible Governing AI Proliferation Frontier AI Regulation: Managing Emerging Risks to Public Safety

Reference 5

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This paper cites Training Compute Thresholds: Features and Functions in AI Regulation.

Towards Responsible Governing AI Proliferation Training Compute Thresholds: Features and Functions in AI Regulation

Reference 6

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This paper cites Technological paradigms and technological trajectories: a suggested interpretation of the determinants and directions of technical change.

Towards Responsible Governing AI Proliferation Technological paradigms and technological trajectories: a suggested interpretation of the determinants and directions of technical change

Reference 7

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This paper cites Anthropic’s Responsible Scaling Policy.

Towards Responsible Governing AI Proliferation Anthropic’s Responsible Scaling Policy

Reference 8

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This paper cites Introducing the Frontier Safety Framework.

Towards Responsible Governing AI Proliferation Introducing the Frontier Safety Framework

Reference 9

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This paper cites Preparedness Framework (Beta).

Towards Responsible Governing AI Proliferation Preparedness Framework (Beta)

Reference 10

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This paper cites AI Governance.

Towards Responsible Governing AI Proliferation AI Governance

Reference 12

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This paper cites Artificial Intelligence Governance for Businesses.

Towards Responsible Governing AI Proliferation Artificial Intelligence Governance for Businesses

Reference 13

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Observation 48e3c525-2bd6-4c8d-920f-6bc5e6784ae0 · outbound

This paper cites Governance of artificial intelligence.

Towards Responsible Governing AI Proliferation Governance of artificial intelligence

Reference 14

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This paper cites International Institutions for Advanced AI.

Towards Responsible Governing AI Proliferation International Institutions for Advanced AI

Reference 15

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This paper cites Model evaluation for extreme risks.

Towards Responsible Governing AI Proliferation Model evaluation for extreme risks

Reference 16

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Observation 54f55d09-9792-4cbd-9196-590683666879 · outbound

This paper cites The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation.

Towards Responsible Governing AI Proliferation The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation

Reference 17

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This paper cites Artificial intelligence and biological misuse: Differentiating risks of language models and biological design tools.

Towards Responsible Governing AI Proliferation Artificial intelligence and biological misuse: Differentiating risks of language models and biological design tools

Reference 18

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This paper cites Building an early warning system for LLM-aided biological threat creation.

Towards Responsible Governing AI Proliferation Building an early warning system for LLM-aided biological threat creation

Reference 19

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This paper cites The threat of offensive ai to organizations.

Towards Responsible Governing AI Proliferation The threat of offensive ai to organizations

Reference 20

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This paper cites Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI.

Towards Responsible Governing AI Proliferation Artificial intelligence (AI) cybersecurity dimensions: a comprehensive framework for understanding adversarial and offensive AI

Reference 21

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This paper cites AI Alignment: A Comprehensive Survey.

Towards Responsible Governing AI Proliferation AI Alignment: A Comprehensive Survey

Reference 22

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This paper cites Foundational Challenges in Assuring Alignment and Safety of Large Language Models.

Towards Responsible Governing AI Proliferation Foundational Challenges in Assuring Alignment and Safety of Large Language Models

Reference 23

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This paper cites Harms of AI.

Towards Responsible Governing AI Proliferation Harms of AI

Reference 24

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This paper cites The incompatible incentives of private-sector AI.

Towards Responsible Governing AI Proliferation The incompatible incentives of private-sector AI

Reference 25

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Observation c4aab8ef-bd1d-4dff-aac3-4ae5f723240a · outbound

This paper cites Towards Responsible Governance of Biological Design Tools.

Towards Responsible Governing AI Proliferation Towards Responsible Governance of Biological Design Tools

Reference 26

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This paper cites A Framework for Fairness: A Systematic Review of Existing Fair AI Solutions.

Towards Responsible Governing AI Proliferation A Framework for Fairness: A Systematic Review of Existing Fair AI Solutions

Reference 27

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Observation 35bd0d72-419e-400f-b6ce-060ad18d6826 · outbound

This paper cites Data, Privacy, and the Individual: A Report for the Cen- ter for the Governance of Change (https://philarchive.org/rec/VLIPM).

Towards Responsible Governing AI Proliferation Data, Privacy, and the Individual: A Report for the Cen- ter for the Governance of Change (https://philarchive.org/rec/VLIPM)

Reference 28

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This paper cites Privacy is Power.

Towards Responsible Governing AI Proliferation Privacy is Power

Reference 29

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Observation 5c2c3f4b-4270-432d-a3b6-d0ca5019fe81 · outbound

This paper cites Account- ability in artificial intelligence: what it is and how it works.

Towards Responsible Governing AI Proliferation Account- ability in artificial intelligence: what it is and how it works

Reference 30

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Observation 295a6c2c-f5b4-4cbc-95b5-0ec27d5c5ef8 · outbound

This paper cites Democratising AI: Multiple meanings, goals, and methods.

Towards Responsible Governing AI Proliferation Democratising AI: Multiple meanings, goals, and methods

Reference 31

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This paper cites The case for strong longter- mism.

Towards Responsible Governing AI Proliferation The case for strong longter- mism

Reference 32

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This paper cites Global AI governance: barriers and pathways for- ward.

Towards Responsible Governing AI Proliferation Global AI governance: barriers and pathways for- ward

Reference 33

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This paper cites AI, governance and ethics: global perspectives.

Towards Responsible Governing AI Proliferation AI, governance and ethics: global perspectives

Reference 34

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This paper cites Artificial intelligence and China’s authoritarian gover- nance.

Towards Responsible Governing AI Proliferation Artificial intelligence and China’s authoritarian gover- nance

Reference 35

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This paper cites AI governance: a research agenda.

Towards Responsible Governing AI Proliferation AI governance: a research agenda

Reference 36

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This paper cites Inductive Risk and Values in Science.

Towards Responsible Governing AI Proliferation Inductive Risk and Values in Science

Reference 37

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This paper cites A framework of blockchain technology adoption: An investigation of challenges and ex- pected value.

Towards Responsible Governing AI Proliferation A framework of blockchain technology adoption: An investigation of challenges and ex- pected value

Reference 38

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Towards Responsible Governing AI Proliferation Digital technologies, innovation, and skills: Emerg- ing trajectories and challenges

Reference 39

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This paper cites A typology of technological change: Technological paradigm theory with validation and generalization from case studies.

Towards Responsible Governing AI Proliferation A typology of technological change: Technological paradigm theory with validation and generalization from case studies

Reference 40

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This paper cites ”The AI Triad and What It Means for National Secu- rity Strategy”.

Towards Responsible Governing AI Proliferation ”The AI Triad and What It Means for National Secu- rity Strategy”

Reference 41

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This paper cites Training Compute-Optimal Large Language Models.

Towards Responsible Governing AI Proliferation Training Compute-Optimal Large Language Models

Reference 42

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This paper cites How predictable is language model benchmark performance?.

Towards Responsible Governing AI Proliferation How predictable is language model benchmark performance?

Reference 43

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This paper cites Racing to the Trillion-Dollar Cluster.

Towards Responsible Governing AI Proliferation Racing to the Trillion-Dollar Cluster

Reference 44

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Towards Responsible Governing AI Proliferation Study of Cloud Security in Hyper- scalers

Reference 45

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This paper cites Ethical issues in the big data industry.

Towards Responsible Governing AI Proliferation Ethical issues in the big data industry

Reference 46

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This paper cites ’An Ecosystem Framework of AI Governance’.

Towards Responsible Governing AI Proliferation ’An Ecosystem Framework of AI Governance’

Reference 47

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This paper cites Oversight for Frontier AI through a Know-Your-Customer Scheme for Compute Providers.

Towards Responsible Governing AI Proliferation Oversight for Frontier AI through a Know-Your-Customer Scheme for Compute Providers

Reference 48

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This paper cites Executive order on the safe, secure, and trustworthy development and use of artificial intelligence.

Towards Responsible Governing AI Proliferation Executive order on the safe, secure, and trustworthy development and use of artificial intelligence

Reference 49

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Towards Responsible Governing AI Proliferation The structure of scientific revolutions

Reference 50

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This paper cites Future-Proofing Frontier AI Regulation.

Towards Responsible Governing AI Proliferation Future-Proofing Frontier AI Regulation

Reference 51

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This paper cites Measuring the Algorithmic Efficiency of Neural Networks.

Towards Responsible Governing AI Proliferation Measuring the Algorithmic Efficiency of Neural Networks

Reference 52

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This paper cites Algorithmic progress in language models.

Towards Responsible Governing AI Proliferation Algorithmic progress in language models

Reference 53

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This paper cites A Survey of Quantization Methods for Efficient Neural Network Inference.

Towards Responsible Governing AI Proliferation A Survey of Quantization Methods for Efficient Neural Network Inference

Reference 54

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Towards Responsible Governing AI Proliferation A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations

Reference 55

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This paper cites A Comprehensive Review of Knowledge Distillation in Computer Vision.

Towards Responsible Governing AI Proliferation A Comprehensive Review of Knowledge Distillation in Computer Vision

Reference 56

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Observation 6af93347-2617-4a87-974b-f05e228a6b81 · outbound

This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

Towards Responsible Governing AI Proliferation Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 57

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This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Towards Responsible Governing AI Proliferation Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 58

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This paper cites Language Models are Few-Shot Learners.

Towards Responsible Governing AI Proliferation Language Models are Few-Shot Learners

Reference 59

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This paper cites OpenELM: An Efficient Language Model Family with Open Training and Inference Framework.

Towards Responsible Governing AI Proliferation OpenELM: An Efficient Language Model Family with Open Training and Inference Framework

Reference 60

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This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Towards Responsible Governing AI Proliferation Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 61

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This paper cites Introducing DBRX: A New State-of-the-Art Open LLM.

Towards Responsible Governing AI Proliferation Introducing DBRX: A New State-of-the-Art Open LLM

Reference 62

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This paper cites Snowflake Arctic: The Best LLM for Enterprise AI — Efficiently Intelligent, Truly Open.

Towards Responsible Governing AI Proliferation Snowflake Arctic: The Best LLM for Enterprise AI — Efficiently Intelligent, Truly Open

Reference 63

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This paper cites The Bitter-er Lesson.

Towards Responsible Governing AI Proliferation The Bitter-er Lesson

Reference 64

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Observation 1524d869-bcbf-4582-b32f-d39327581d6f · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Towards Responsible Governing AI Proliferation KAN: Kolmogorov-Arnold Networks

Reference 65

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Observation 8bb5c4e3-df5e-4716-b776-6c96ce346ce3 · outbound

This paper cites Position: Leverage Foundational Models for Black-Box Optimization.

Towards Responsible Governing AI Proliferation Position: Leverage Foundational Models for Black-Box Optimization

Reference 66

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Observation 4b10a59c-f46a-4764-b705-57f07a328c06 · outbound

This paper cites MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT.

Towards Responsible Governing AI Proliferation MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT

Reference 68

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Observation 21551fe3-a9e7-4a8f-860e-e4609290fd4a · outbound

This paper cites Phi 3 and Arctic: Outlier LMs are hints.

Towards Responsible Governing AI Proliferation Phi 3 and Arctic: Outlier LMs are hints

Reference 69

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Observation 18dec2b8-1fb5-47dc-a659-56db1cf1a1bc · outbound

This paper cites Increased Compute Efficiency and the Diffusion of AI Capabilities.

Towards Responsible Governing AI Proliferation Increased Compute Efficiency and the Diffusion of AI Capabilities

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:47:49.341079Z

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Observation a98c830e-6b25-404b-a6ce-6c40ba03e9d0 · outbound

This paper cites GPT-2: The Strange Debacle Surrounding Mystery ‘OpenAI’ Chatbot.

Towards Responsible Governing AI Proliferation GPT-2: The Strange Debacle Surrounding Mystery ‘OpenAI’ Chatbot

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.489828Z

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Observation 9d17ea72-34d0-4137-9f07-ea31a8990dc4 · outbound

This paper cites Responsible Reporting for Frontier AI Development.

Towards Responsible Governing AI Proliferation Responsible Reporting for Frontier AI Development

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.494241Z

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Observation 21e734d8-e05c-4c2d-8f6f-aa911c8aa6f7 · outbound

This paper cites Responsible Reporting for Frontier AI Development.

Towards Responsible Governing AI Proliferation Responsible Reporting for Frontier AI Development

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.499616Z

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Observation edf004df-6d90-4c4f-9dfd-41acdb48ad1e · outbound

This paper cites Qwen Technical Report.

Towards Responsible Governing AI Proliferation Qwen Technical Report

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.505076Z

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Observation 028bf793-331f-4adb-a577-29a296c753eb · outbound

This paper cites Through partnership with IBM, Saudi Data and Artificial Intelli- gence Authority (SDAIA) launches a groundbreaking Arabic AI model to the Middle East.

Towards Responsible Governing AI Proliferation Through partnership with IBM, Saudi Data and Artificial Intelli- gence Authority (SDAIA) launches a groundbreaking Arabic AI model to the Middle East

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.508950Z

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Observation d02e2a69-b9f0-4e11-9334-bcf592b47006 · outbound

This paper cites Abu Dhabi makes its Falcon 40B AI model open sourc.

Towards Responsible Governing AI Proliferation Abu Dhabi makes its Falcon 40B AI model open sourc

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.514022Z

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Observation 62b32b48-95ee-4534-b0a6-c33adbd9828d · outbound

This paper cites Near to Mid-term Risks and Opportunities of Open-Source Generative AI.

Towards Responsible Governing AI Proliferation Near to Mid-term Risks and Opportunities of Open-Source Generative AI

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.518086Z

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Observation 42deb9cd-7a4e-4403-8259-de1cf8b60f7e · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

Towards Responsible Governing AI Proliferation Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.522067Z

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Observation e053423e-c0c9-44cc-8a28-522036f3b65b · outbound

This paper cites Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding.

Towards Responsible Governing AI Proliferation Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.526781Z

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Observation 01ef59ea-a68a-4cab-82b4-bc9d73141726 · outbound

This paper cites AI capabilities can be significantly improved without expensive retraining.

Towards Responsible Governing AI Proliferation AI capabilities can be significantly improved without expensive retraining

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.531312Z

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Observation 95bf8efc-de6f-4c31-9bdf-15e03f276be2 · outbound

This paper cites Sholto Douglas and Trenton Bricken - How to Build and Understand GPT-7’s Mind (https://www.dwarkeshpatel.com/p/sholto-douglas- trenton-bricken).

Towards Responsible Governing AI Proliferation Sholto Douglas and Trenton Bricken - How to Build and Understand GPT-7’s Mind (https://www.dwarkeshpatel.com/p/sholto-douglas- trenton-bricken)

Reference 81

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Observation 94fb28ef-ae52-441c-a5e1-c51be44bf5dd · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Towards Responsible Governing AI Proliferation Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.541071Z

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Observation 0062efa6-87c6-4d4f-ae14-56e148a9045b · outbound

This paper cites Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey.

Towards Responsible Governing AI Proliferation Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.544788Z

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Observation d434fdc6-0c7c-4536-a13a-37f62617fdf7 · outbound

This paper cites Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!.

Towards Responsible Governing AI Proliferation Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.549569Z

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Observation 8192c129-7341-47d8-b795-b593ba295c8c · outbound

This paper cites Evolutionary Optimization of Model Merging Recipes.

Towards Responsible Governing AI Proliferation Evolutionary Optimization of Model Merging Recipes

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.554436Z

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Observation 1a6d9387-d3a4-4559-979a-aa0e97a5504e · outbound

This paper cites Evolutionary Optimization of Model Merging Recipes.

Towards Responsible Governing AI Proliferation Evolutionary Optimization of Model Merging Recipes

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.558557Z

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Observation b6a5f4c6-4ca9-45dc-abed-0665f967335d · outbound

This paper cites Command R+ (https://docs.cohere.com/docs/command-r-plus).

Towards Responsible Governing AI Proliferation Command R+ (https://docs.cohere.com/docs/command-r-plus)

Reference 87

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Observation 829f843c-5669-4e19-9ac2-e89dd04f099b · outbound

This paper cites Github Copilot (https://github.com/features/copilot).

Towards Responsible Governing AI Proliferation Github Copilot (https://github.com/features/copilot)

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.569314Z

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Observation c1ead822-c409-4848-b26b-407af593f403 · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Towards Responsible Governing AI Proliferation AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.573566Z

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Observation a4a60d7d-2172-46a7-9f15-eeefdd4b5c19 · outbound

This paper cites Training Language Model Agents without Modi- fying Language Models.

Towards Responsible Governing AI Proliferation Training Language Model Agents without Modi- fying Language Models

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.578082Z

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Observation 00beb18c-9f95-4fe9-b921-fba4da18ee4d · outbound

This paper cites Frontier Safety Framework.

Towards Responsible Governing AI Proliferation Frontier Safety Framework

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.581617Z

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Observation 254ee1f0-e1c8-4a2a-ad4e-29febbd68614 · outbound

This paper cites Multi-Stage Prompting for Next Best Agent Rec- ommendations in Adaptive Workflows.

Towards Responsible Governing AI Proliferation Multi-Stage Prompting for Next Best Agent Rec- ommendations in Adaptive Workflows

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.585421Z

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Observation 2386fa00-d712-4049-a3d7-7e1e726765f6 · outbound

This paper cites Deep reinforcement learning from human preferences.

Towards Responsible Governing AI Proliferation Deep reinforcement learning from human preferences

Reference 93

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Observation 26e4fef4-f17e-4ba3-9b40-242b8a5e026c · outbound

This paper cites Distributing and Democratizing Institutional Power Through Decentralization.

Towards Responsible Governing AI Proliferation Distributing and Democratizing Institutional Power Through Decentralization

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.593296Z

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Observation 7371440f-8ba3-4d26-98a7-b45c46a3d00b · outbound

This paper cites Big AI can centralize decision-making and power, and that’sa problem.

Towards Responsible Governing AI Proliferation Big AI can centralize decision-making and power, and that’sa problem

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.597622Z

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Observation d24f0f6a-2382-49ba-b029-bfaf1f3e4515 · outbound

This paper cites Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations.

Towards Responsible Governing AI Proliferation Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.601255Z

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Observation c4e415c2-08dd-44b8-8630-9cc2121587de · outbound

This paper cites Distributed, decentralized, and democratized artificial intelligence.

Towards Responsible Governing AI Proliferation Distributed, decentralized, and democratized artificial intelligence

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.606710Z

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Observation aebce98d-64ef-4ffd-8bf4-c27a1845a309 · outbound

This paper cites A Review on Building Blocks of Decentralized Artificial Intelligence.

Towards Responsible Governing AI Proliferation A Review on Building Blocks of Decentralized Artificial Intelligence

Reference 98

Resolution: verified exact; local_arxiv, observed 2026-08-11T12:47:49.202165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 4b80498d-fb6e-4eb4-9276-6d379c319027 · outbound

This paper cites TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems.

Towards Responsible Governing AI Proliferation TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.614860Z

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Observation f9878fd9-c777-4e21-bf92-5a8c0cf4fc63 · outbound

This paper cites Distributed Machine Learning on Akash Network With Ray (https://akash.network/).

Towards Responsible Governing AI Proliferation Distributed Machine Learning on Akash Network With Ray (https://akash.network/)

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-11T12:47:48.618571Z

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Observation 423f3130-4b37-4e6e-86ba-4f2f5d3f9191 · outbound

This paper cites Decentralized Physical Infrastructure Network (DePIN): Challenges and Opportunities.

Towards Responsible Governing AI Proliferation Decentralized Physical Infrastructure Network (DePIN): Challenges and Opportunities

Reference 101

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Observation 29a1b881-efab-406d-99ee-36a67284128f · outbound

This paper cites Golem (https://www.golem.network/).

Towards Responsible Governing AI Proliferation Golem (https://www.golem.network/)

Reference 102

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