Why_this_webapp Bibliography

Dual Governance: The intersection of centralized regulation and crowdsourced safety mechanisms for Generative AI / 2308.04448 / ISBN:https://doi.org/10.48550/arXiv.2308.04448 / Published by ArXiv / on (web) Publishing site

5 Crowdsourced safety mechanism
7 Limitations

The Cambridge Law Corpus: A Corpus for Legal AI Research / 2309.12269 / ISBN:https://doi.org/10.48550/arXiv.2309.12269 / Published by ArXiv / on (web) Publishing site

Cambridge Law Corpus: Datasheet

A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges / 2310.16360 / ISBN:https://doi.org/10.48550/arXiv.2310.16360 / Published by ArXiv / on (web) Publishing site

I. Introduction

Case Repositories: Towards Case-Based Reasoning for AI Alignment / 2311.10934 / ISBN:https://doi.org/10.48550/arXiv.2311.10934 / Published by ArXiv / on (web) Publishing site

2 Proposed Process

Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective / 2311.18252 / ISBN:https://doi.org/10.48550/arXiv.2311.18252 / Published by ArXiv / on (web) Publishing site

2 Legal Basis of Privacy and Copyright Concerns over Generative AI
3 Mapping Challenges throughout the Data Lifecycle
4 Lifecycle Approaches

Ethical Considerations Towards Protestware / 2306.10019 / ISBN:https://doi.org/10.48550/arXiv.2306.10019 / Published by ArXiv / on (web) Publishing site

III. Ethics: a primer
IV. Guidelines for promoting ethical responsibility

Business and ethical concerns in domestic Conversational Generative AI-empowered multi-robot systems / 2401.09473 / ISBN:https://doi.org/10.48550/arXiv.2401.09473 / Published by ArXiv / on (web) Publishing site

2 Background

FAIR Enough How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training? / 2401.11033 / ISBN:https://doi.org/10.48550/arXiv.2401.11033 / Published by ArXiv / on (web) Publishing site

2 FAIR Data Principles: Theoretical Background and Significance
4 Framework for FAIR Data Principles Integration in LLM Development

A Scoping Study of Evaluation Practices for Responsible AI Tools: Steps Towards Effectiveness Evaluations / 2401.17486 / ISBN:https://doi.org/10.48550/arXiv.2401.17486 / Published by ArXiv / on (web) Publishing site

3 Methods

(A)I Am Not a Lawyer, But...: Engaging Legal Experts towards Responsible LLM Policies for Legal Advice / 2402.01864 / ISBN:https://doi.org/10.48550/arXiv.2402.01864 / Published by ArXiv / on (web) Publishing site

2 Related work and our approach

Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications / 2402.12216 / ISBN:https://doi.org/10.48550/arXiv.2402.12216 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Related Work

Evaluation Ethics of LLMs in Legal Domain / 2403.11152 / ISBN:https://doi.org/10.48550/arXiv.2403.11152 / Published by ArXiv / on (web) Publishing site

1 Introduction

Is Your AI Truly Yours? Leveraging Blockchain for Copyrights, Provenance, and Lineage / 2404.06077 / ISBN:https://doi.org/10.48550/arXiv.2404.06077 / Published by ArXiv / on (web) Publishing site

Abstract
I. Introduction
II. Preliminaries
III. Proposed Design: IBIS
IV. Detailed Construction
V. Implementation on DAML
VI. Evaluation
VII. Conclusion

Large Language Model Supply Chain: A Research Agenda / 2404.12736 / ISBN:https://doi.org/10.48550/arXiv.2404.12736 / Published by ArXiv / on (web) Publishing site

3 LLM Infrastructure

A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI / 2405.04333 / ISBN:https://doi.org/10.48550/arXiv.2405.04333 / Published by ArXiv / on (web) Publishing site

3. A Spectrum of Scenarios of Open Data for Generative AI

MoralBench: Moral Evaluation of LLMs / 2406.04428 / Published by ArXiv / on (web) Publishing site

Appendix

Federated Learning driven Large Language Models for Swarm Intelligence: A Survey / 2406.09831 / ISBN:https://doi.org/10.48550/arXiv.2406.09831 / Published by ArXiv / on (web) Publishing site

I. Introduction

Documenting Ethical Considerations in Open Source AI Models / 2406.18071 / ISBN:https://doi.org/10.48550/arXiv.2406.18071 / Published by ArXiv / on (web) Publishing site

4 RESULTS

Surveys Considered Harmful? Reflecting on the Use of Surveys in AI Research, Development, and Governance / 2408.01458 / ISBN:https://doi.org/10.48550/arXiv.2408.01458 / Published by ArXiv / on (web) Publishing site

5 Discussion

Between Copyright and Computer Science: The Law and Ethics of Generative AI / 2403.14653 / ISBN:https://doi.org/10.48550/arXiv.2403.14653 / Published by ArXiv / on (web) Publishing site

III. A Guide for Data in LLM Research

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources / 2406.16746 / ISBN:https://doi.org/10.48550/arXiv.2406.16746 / Published by ArXiv / on (web) Publishing site

1 Introduction
2 Methodology & Guidelines
3 Data Sources
4 Data Preparation
5 Data Documentation and Release
9 Model Release & Monitoring

Catalog of General Ethical Requirements for AI Certification / 2408.12289 / ISBN:https://doi.org/10.48550/arXiv.2408.12289 / Published by ArXiv / on (web) Publishing site

9 Sustainability (SU)

AI-Press: A Multi-Agent News Generating and Feedback Simulation System Powered by Large Language Models / 2410.07561 / ISBN:https://doi.org/10.48550/arXiv.2410.07561 / Published by ArXiv / on (web) Publishing site

1 Introduction

From human-centered to social-centered artificial intelligence: Assessing ChatGPT's impact through disruptive events / 2306.00227 / ISBN:https://doi.org/10.48550/arXiv.2306.00227 / Published by ArXiv / on (web) Publishing site

Introduction

Learning Human-like Representations to Enable Learning Human Values / 2312.14106 / ISBN:https://doi.org/10.48550/arXiv.2312.14106 / Published by ArXiv / on (web) Publishing site

A. Appendix

TRIAGE: Ethical Benchmarking of AI Models Through Mass Casualty Simulations / 2410.18991 / ISBN:https://doi.org/10.48550/arXiv.2410.18991 / Published by ArXiv / on (web) Publishing site

Appendices

Improving governance outcomes through AI documentation: Bridging theory and practice / 2409.08960 / ISBN:https://doi.org/10.48550/arXiv.2409.08960 / Published by ArXiv / on (web) Publishing site

Towards A Litmus Test for Common Sense / 2501.09913 / ISBN:https://doi.org/10.48550/arXiv.2501.09913 / Published by ArXiv / on (web) Publishing site

4 An Axiomatic Litmus Test for Common Sense
7 Mathematical Formulation for LLMs and AI
8 Ensuring a Path to Safe and Trustworthy AI

A Critical Field Guide for Working with Machine Learning Datasets / 2501.15491 / ISBN:https://doi.org/10.48550/arXiv.2501.15491 / Published by ArXiv / on (web) Publishing site

2. Benefits: Why Approach Datasets Critically?

Responsible Generative AI Use by Product Managers: Recoupling Ethical Principles and Practices / 2501.16531 / ISBN:https://doi.org/10.48550/arXiv.2501.16531 / Published by ArXiv / on (web) Publishing site

5. Findings

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription / 2502.04356 / ISBN:https://doi.org/10.48550/arXiv.2502.04356 / Published by ArXiv / on (web) Publishing site

II. Background

Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives / 2502.16841 / ISBN:https://doi.org/10.48550/arXiv.2502.16841 / Published by ArXiv / on (web) Publishing site

3 Data Documentation

Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Models / 2502.18505 / ISBN:https://doi.org/10.48550/arXiv.2502.18505 / Published by ArXiv / on (web) Publishing site

1. Introduction
2. Methodology
3. Results
5. Conclusion

Who Owns the Output? Bridging Law and Technology in LLMs Attribution / 2504.01032 / ISBN:https://doi.org/10.48550/arXiv.2504.01032 / Published by ArXiv / on (web) Publishing site

2 Legal Background

A Comprehensive Survey on Integrating Large Language Models with Knowledge-Based Methods / 2501.13947 / ISBN:https://doi.org/10.48550/arXiv.2501.13947 / Published by ArXiv / on (web) Publishing site

1. Introduction

Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation / 2502.05151 / ISBN:https://doi.org/10.48550/arXiv.2502.05151 / Published by ArXiv / on (web) Publishing site

3 AI Support for Individual Topics and Tasks

Ethical AI in the Healthcare Sector: Investigating Key Drivers of Adoption through the Multi-Dimensional Ethical AI Adoption Model (MEAAM) / 2505.02062 / ISBN:https://doi.org/10.9734/ajmah/2025/v23i51228 / Published by ArXiv / on (web) Publishing site

Appendix

Beyond Individual UX: Defining Group Experience(GX) as a New Paradigm for Group-centered AI / 2505.12780 / ISBN:https://doi.org/10.48550/arXiv.2505.12780 / Published by ArXiv / on (web) Publishing site

Abstract

From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery / 2505.13259 / ISBN:https://doi.org/10.48550/arXiv.2505.13259 / Published by ArXiv / on (web) Publishing site

6 Challenges and Future Directions

TEDI: Trustworthy and Ethical Dataset Indicators to Analyze and Compare Dataset Documentation / 2505.17841 / ISBN:https://doi.org/10.48550/arXiv.2505.17841 / Published by ArXiv / on (web) Publishing site

5 Discussion and Limitations
Appendix