SOTAVerified

Ethics

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 832 papers

TitleStatusHype
A Blockchain-Enabled Approach to Cross-Border Compliance and Trust—0
Anonymous Attention and Abuse—0
Deontic Temporal Logic for Formal Verification of AI Ethics—0
The global consensus on the risk management of autonomous driving—0
A survey of textual cyber abuse detection using cutting-edge language models and large language models—0
A Metasemantic-Metapragmatic Framework for Taxonomizing Multimodal Communicative Alignment—0
Measuring Large Language Models Capacity to Annotate Journalistic Sourcing—0
Complement or substitute? How AI increases the demand for human skills—0
Ethics and Technical Aspects of Generative AI Models in Digital Content Creation—0
The Only Way is Ethics: A Guide to Ethical Research with Large Language ModelsCode0
Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents—0
Towards an Environmental Ethics of Artificial Intelligence—0
Chinese SafetyQA: A Safety Short-form Factuality Benchmark for Large Language Models—0
Multimodal Approaches to Fair Image Classification: An Ethical Perspective—0
Machines of Meaning—0
From Principles to Practice: A Deep Dive into AI Ethics and Regulations—0
Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground—0
A History of Philosophy in Colombia through Topic ModellingCode0
On Privacy, Security, and Trustworthiness in Distributed Wireless Large AI Models (WLAM)—0
Trustworthy artificial intelligence in the energy sector: Landscape analysis and evaluation framework—0
Inducing Human-like Biases in Moral Reasoning Language Models—0
On the Fairness, Diversity and Reliability of Text-to-Image Generative Models—0
Privacy-Preserving Video Anomaly Detection: A Survey—0
Value Imprint: A Technique for Auditing the Human Values Embedded in RLHF Datasets—0
Towards a Practical Ethics of Generative AI in Creative Production Processes—0
Progressive Generalization Risk Reduction for Data-Efficient Causal Effect EstimationCode0
Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents—0
Ethical Concern Identification in NLP: A Corpus of ACL Anthology Ethics Statements—0
Challenges in Guardrailing Large Language Models for Science—0
Beyond Keywords: A Context-based Hybrid Approach to Mining Ethical Concern-related App Reviews—0
Balancing Power and Ethics: A Framework for Addressing Human Rights Concerns in Military AI—0
Evaluating the Economic Implications of Using Machine Learning in Clinical Psychiatry—0
Delegating Responsibilities to Intelligent Autonomous Systems: Challenges and Benefits—0
AI Ethics by Design: Implementing Customizable Guardrails for Responsible AI Development—0
User-wise Perturbations for User Identity Protection in EEG-Based BCIs—0
Introduction to AI Safety, Ethics, and Society—0
Automated Trustworthiness Oracle Generation for Machine Learning Text Classifiers—0
Assessing the Auditability of AI-integrating Systems: A Framework and Learning Analytics Case Study—0
Do Large Language Models Align with Core Mental Health Counseling Competencies?—0
Moral Agency in Silico: Exploring Free Will in Large Language Models—0
Quantifying Risk Propensities of Large Language Models: Ethical Focus and Bias Detection through Role-Play—0
Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI—0
From Efficiency to Equity: Measuring Fairness in Preference Learning—0
Computational Grounding of Responsibility Attribution and Anticipation in LTLf—0
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 Scarce—0
A Comparative Analysis on Ethical Benchmarking in Large Language Models—0
Prompt Engineering a Schizophrenia Chatbot: Utilizing a Multi-Agent Approach for Enhanced Compliance with Prompt Instructions—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