SOTAVerified

Ethics

Papers

Showing 426450 of 832 papers

TitleStatusHype
Applying Standards to Advance Upstream & Downstream Ethics in Large Language Models0
Milestones in Autonomous Driving and Intelligent Vehicles Part II: Perception and Planning0
The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practices0
AI Imagery and the Overton Window0
Responsible Design Patterns for Machine Learning PipelinesCode0
RE-centric Recommendations for the Development of Trustworthy(er) Autonomous Systems0
AI Audit: A Card Game to Reflect on Everyday AI Systems0
Mapping ChatGPT in Mainstream Media to Unravel Jobs and Diversity Challenges: Early Quantitative Insights through Sentiment Analysis and Word Frequency Analysis0
Deep Learning and Ethics0
Science in the Era of ChatGPT, Large Language Models and Generative AI: Challenges for Research Ethics and How to Respond0
On the Origins of Bias in NLP through the Lens of the Jim Code0
Walking the Walk of AI Ethics: Organizational Challenges and the Individualization of Risk among Ethics Entrepreneurs0
Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems0
Milestones in Autonomous Driving and Intelligent Vehicles Part I: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors0
The Ethics of AI in Games0
ChatGPT: Vision and Challenges0
Asymmetric quantum decision-making0
The Future of Artificial Intelligence (AI) and Machine Learning (ML) in Landscape Design: A Case Study in Coastal Virginia, USA0
Uncertain Machine Ethical Decisions Using Hypothetical RetrospectionCode0
Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation0
Towards ethical multimodal systems0
An Audit Framework for Adopting AI-Nudging on Children0
Organizational Governance of Emerging Technologies: AI Adoption in Healthcare0
Towards a Praxis for Intercultural Ethics in Explainable AI0
A Group-Specific Approach to NLP for Hate Speech DetectionCode0
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Benchmark Results

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