SOTAVerified

Ethics

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 576–600 of 832 papers

TitleStatusHype
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
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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