SOTAVerified

Ethics

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 451–500 of 832 papers

TitleStatusHype
Moral Sparks in Social Media Narratives—0
More-than-Human Storytelling: Designing Longitudinal Narrative Engagements with Generative AI—0
Multi-Agent Risks from Advanced AI—0
Multi Layered Autonomy and AI Ecologies in Robotic Art Installations—0
Multimodal Approaches to Fair Image Classification: An Ethical Perspective—0
My Answer Is NOT 'Fair': Mitigating Social Bias in Vision-Language Models via Fair and Biased Residuals—0
Navigating LLM Ethics: Advancements, Challenges, and Future Directions—0
Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents—0
Non-Additive Axiologies in Large Worlds—0
None of the Above, Less of the Right: Parallel Patterns between Humans and LLMs on Multi-Choice Questions Answering—0
No NLP Task Should be an Island: Multi-disciplinarity for Diversity in News Recommender Systems—0
Normative Conditional Reasoning as a Fragment of HOL—0
Nutrition Facts, Drug Facts, and Model Facts: Putting AI Ethics into Practice in Gun Violence Research—0
On Consequentialism and Fairness—0
One Formalization of Virtue Ethics via Learning—0
On General Language Understanding—0
On Quantified Modal Theorem Proving for Modeling Ethics—0
On Text-based Personality Computing: Challenges and Future Directions—0
On the causality-preservation capabilities of generative modelling—0
On the Computational Complexity of Ethics: Moral Tractability for Minds and Machines—0
On the Efficiency of Ethics as a Governing Tool for Artificial Intelligence—0
On the Ethics of Building AI in a Responsible Manner—0
On the ethics of constructing conscious AI—0
On the Fairness, Diversity and Reliability of Text-to-Image Generative Models—0
On the Limitations and Prospects of Machine Unlearning for Generative AI—0
On the Machine Learning of Ethical Judgments from Natural Language—0
On the Origins of Bias in NLP through the Lens of the Jim Code—0
On the Perception of Plagiarism in Academia: Context and Intent—0
On Privacy, Security, and Trustworthiness in Distributed Wireless Large AI Models (WLAM)—0
Open-domain Dialogue Generation: What We Can Do, Cannot Do, And Should Do Next—0
Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents—0
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare—0
Oxford Handbook on AI Ethics Book Chapter on Race and Gender—0
P4AI: Approaching AI Ethics through Principlism—0
Path To Gain Functional Transparency In Artificial Intelligence With Meaningful Explainability—0
Perceptions of the Fourth Industrial Revolution and Artificial Intelligence Impact on Society—0
Personalized Detection of Cognitive Biases in Actions of Users from Their Logs: Anchoring and Recency Biases—0
Perspectives and Ethics of the Autonomous Artificial Thinking Systems—0
Position: Olfaction Standardization is Essential for the Advancement of Embodied Artificial Intelligence—0
Precision Health Data: Requirements, Challenges and Existing Techniques for Data Security and Privacy—0
Prediction Accuracy and Autonomy—0
Prescriptive Machine Learning for Automated Decision Making: Challenges and Opportunities—0
Principled Frameworks for Evaluating Ethics in NLP Systems—0
Prioritizing High-Consequence Biological Capabilities in Evaluations of Artificial Intelligence Models—0
Prioritizing Policies for Furthering Responsible Artificial Intelligence in the United States—0
Prismal view of ethics—0
Privacy Ethics Alignment in AI: A Stakeholder-Centric Based Framework for Ethical AI—0
Privacy-Preserving Video Anomaly Detection: A Survey—0
PrivPAS: A real time Privacy-Preserving AI System and applied ethics—0
Proceedings 39th International Conference on Logic Programming—0
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All datasetsETHICSEthics (per ethics)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RuGPT-3 LargeAccuracy68.6—Unverified
2RuGPT-3 MeduimAccuracy68.3—Unverified
3RuGPT-3 SmallAccuracy55.5—Unverified
4Human benchmarkAccuracy52.9—Unverified
#ModelMetricClaimedVerifiedStatus
1Human benchmarkAccuracy67.6—Unverified
2RuGPT-3 SmallAccuracy60.9—Unverified
3RuGPT-3 LargeAccuracy44.9—Unverified
4RuGPT-3 MediumAccuracy44.1—Unverified