SOTAVerified

Ethics

Papers

Showing 176200 of 832 papers

TitleStatusHype
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect EstimationCode0
Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents0
Ethical Concern Identification in NLP: A Corpus of ACL Anthology Ethics Statements0
Challenges in Guardrailing Large Language Models for Science0
Beyond Keywords: A Context-based Hybrid Approach to Mining Ethical Concern-related App Reviews0
Balancing Power and Ethics: A Framework for Addressing Human Rights Concerns in Military AI0
Evaluating the Economic Implications of Using Machine Learning in Clinical Psychiatry0
Delegating Responsibilities to Intelligent Autonomous Systems: Challenges and Benefits0
AI Ethics by Design: Implementing Customizable Guardrails for Responsible AI Development0
User-wise Perturbations for User Identity Protection in EEG-Based BCIs0
Introduction to AI Safety, Ethics, and Society0
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers0
Assessing the Auditability of AI-integrating Systems: A Framework and Learning Analytics Case Study0
Do Large Language Models Align with Core Mental Health Counseling Competencies?0
Moral Agency in Silico: Exploring Free Will in Large Language Models0
Quantifying Risk Propensities of Large Language Models: Ethical Focus and Bias Detection through Role-Play0
Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI0
From Efficiency to Equity: Measuring Fairness in Preference Learning0
Computational Grounding of Responsibility Attribution and Anticipation in LTLf0
Unveiling Large Language Models Generated Texts: A Multi-Level Fine-Grained Detection FrameworkCode0
Ethics Whitepaper: Whitepaper on Ethical Research into Large Language ModelsCode0
Data Defenses Against Large Language ModelsCode0
Building Better: Avoiding Pitfalls in Developing Language Resources when Data is Scarce0
A Comparative Analysis on Ethical Benchmarking in Large Language Models0
Prompt Engineering a Schizophrenia Chatbot: Utilizing a Multi-Agent Approach for Enhanced Compliance with Prompt Instructions0
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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