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Tag: sasha
Bibliography items where occurs: 20
- The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / Version released on 2022-05-02 / on (web) Publishing site
- 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 / Version released on 2024-09-03 / on (web) Publishing site
- Concerns and Values in Human-Robot Interactions: A Focus on Social Robotics / 2501.05628 / ISBN:https://doi.org/10.48550/arXiv.2501.05628 / Published by ArXiv / Version released on 2025-12-07 / on (web) Publishing site
- A Critical Field Guide for Working with Machine Learning Datasets / 2501.15491 / ISBN:https://doi.org/10.48550/arXiv.2501.15491 / Published by ArXiv / Version released on 2025-01-26 / on (web) Publishing site
- FairT2I: Mitigating Social Bias in Text-to-Image Generation via Large Language Model-Assisted Detection and Attribute Rebalancing / 2502.03826 / ISBN:https://doi.org/10.48550/arXiv.2502.03826 / Published by ArXiv / Version released on 2025-08-15 / on (web) Publishing site
- On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective / 2502.14296 / ISBN:https://doi.org/10.48550/arXiv.2502.14296 / Published by ArXiv / Version released on 2025-09-30 / on (web) Publishing site
- Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives
/ 2502.16841 / ISBN:https://doi.org/10.48550/arXiv.2502.16841 / Published by ArXiv / Version released on 2026-01-14 / on (web) Publishing site
- Bridging the Gap: Integrating Ethics and Environmental Sustainability in AI Research and Practice / 2504.00797 / ISBN:https://doi.org/10.48550/arXiv.2504.00797 / Published by ArXiv / Version released on 2025-04-01 / on (web) Publishing site
- Locating Risk: Task Designers and the Challenge of Risk Disclosure in RAI Content Work / 2505.24246 / ISBN:https://doi.org/10.48550/arXiv.2505.24246 / Published by ArXiv / Version released on 2026-03-31 / on (web) Publishing site
- A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications / 2506.12594 / ISBN:https://doi.org/10.48550/arXiv.2506.12594 / Published by ArXiv / Version released on 2025-06-14 / on (web) Publishing site
- Ask before you Build: Rethinking AI-for-Good in Human Trafficking Interventions / 2506.22512 / ISBN:https://doi.org/10.48550/arXiv.2506.22512 / Published by ArXiv / Version released on 2025-06-26 / on (web) Publishing site
- Challenges of Trustworthy Federated Learning: What's Done, Current Trends and Remaining Work / 2507.15796 / ISBN:https://doi.org/10.48550/arXiv.2507.15796 / Published by ArXiv / Version released on 2025-07-21 / on (web) Publishing site
- REConnect: Participatory RE that Matters / 2509.01006 / ISBN:https://doi.org/10.48550/arXiv.2509.01006 / Published by ArXiv / Version released on 2025-08-31 / on (web) Publishing site
- Fully Autonomous AI Agents Should Not be Developed / 2502.02649 / ISBN:https://doi.org/10.48550/arXiv.2502.02649 / Published by ArXiv / Version released on 2025-10-20 / on (web) Publishing site
- Making Power Explicable in AI: Analyzing, Understanding, and Redirecting Power to Operationalize Ethics in AI Technical Practice / 2510.10588 / ISBN:https://doi.org/10.48550/arXiv.2510.10588 / Published by ArXiv / Version released on 2025-10-12 / on (web) Publishing site
- Irresponsible AI: big tech's influence on AI research and associated impacts / 2512.03077 / ISBN:https://doi.org/10.48550/arXiv.2512.03077 / Published by ArXiv / Version released on 2025-11-27 / on (web) Publishing site
- Unsupervised Elicitation of Moral Values from Language Models / 2601.17728 / ISBN:https://doi.org/10.48550/arXiv.2601.17728 / Published by ArXiv / Version released on 2026-01-25 / on (web) Publishing site
- Reliable and Responsible Foundation Models: A Comprehensive Survey / 2602.08145 / ISBN:https://doi.org/10.48550/arXiv.2602.08145 / Published by ArXiv / Version released on 2026-02-04 / on (web) Publishing site
- Dark and Bright Side of Participatory Red-Teaming with Targets of Stereotyping for Eliciting Harmful Behaviors from Large Language Models / 2602.19124 / ISBN:https://doi.org/10.48550/arXiv.2602.19124 / Version released on 2026-02-22 / on (web) Publishing site
- Must Read: A Comprehensive Survey of Computational Persuasion / 2505.07775 / ISBN:https://doi.org/10.48550/arXiv.2505.07775 / Version released on 2026-03-23 / on (web) Publishing site