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Tag: outperforms
Bibliography items where occurs: 61
- The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
- Chapter 3 Technical AI Ethics
Appendix - Rethinking Machine Ethics -- Can LLMs Perform Moral Reasoning through the Lens of Moral Theories? / 2308.15399 / ISBN:https://doi.org/10.48550/arXiv.2308.15399 / Published by ArXiv / on (web) Publishing site
- 4 Experiment
- A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics / 2310.05694 / ISBN:https://doi.org/10.48550/arXiv.2310.05694 / Published by ArXiv / on (web) Publishing site
- 2. What LLMs can do for healthcare? from fundamental tasks to
advanced applications
3. From PLMs to LLMs for healthcare - An Evaluation of GPT-4 on the ETHICS Dataset / 2309.10492 / ISBN:https://doi.org/10.48550/arXiv.2309.10492 / Published by ArXiv / on (web) Publishing site
- 3 Results
- Specific versus General Principles for Constitutional AI / 2310.13798 / ISBN:https://doi.org/10.48550/arXiv.2310.13798 / Published by ArXiv / on (web) Publishing site
- 2 AI feedback on specific problematic AI traits
3 Generalization from a Simple Good for Humanity Principle - Unpacking the Ethical Value Alignment in Big Models / 2310.17551 / ISBN:https://doi.org/10.48550/arXiv.2310.17551 / Published by ArXiv / on (web) Publishing site
- 3 Investigating the Ethical Values of
Large Language Models
- Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing / 2304.02017 / ISBN:https://doi.org/10.48550/arXiv.2304.02017 / Published by ArXiv / on (web) Publishing site
- 2 Overview of ChatGPT and its capabilities
- She had Cobalt Blue Eyes: Prompt Testing to Create Aligned and Sustainable Language Models / 2310.18333 / ISBN:https://doi.org/10.48550/arXiv.2310.18333 / Published by ArXiv / on (web) Publishing site
- 4 Empirical Evaluation and Outcomes
5 Conclusion - How Trustworthy are Open-Source LLMs? An Assessment under Malicious Demonstrations Shows their Vulnerabilities / 2311.09447 / ISBN:https://doi.org/10.48550/arXiv.2311.09447 / Published by ArXiv / on (web) Publishing site
- 4 Experiments
- Prudent Silence or Foolish Babble? Examining Large Language Models' Responses to the Unknown / 2311.09731 / ISBN:https://doi.org/10.48550/arXiv.2311.09731 / Published by ArXiv / on (web) Publishing site
- D Additional Results and Figures
- Survey on AI Ethics: A Socio-technical Perspective / 2311.17228 / ISBN:https://doi.org/10.48550/arXiv.2311.17228 / Published by ArXiv / on (web) Publishing site
- 4 Fairness and equity
- Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
- 2. LLMs in cognitive and behavioral psychology
- Synthetic Data in AI: Challenges, Applications, and Ethical Implications / 2401.01629 / ISBN:https://doi.org/10.48550/arXiv.2401.01629 / Published by ArXiv / on (web) Publishing site
- 3. The usage of synthetic data
- MULTI-CASE: A Transformer-based Ethics-aware Multimodal Investigative Intelligence Framework / 2401.01955 / ISBN:https://doi.org/10.48550/arXiv.2401.01955 / Published by ArXiv / on (web) Publishing site
- V. Evaluation
References - Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site
- Discussion
- FAIR Enough How Can We Develop and Assess a FAIR-Compliant Dataset for Large Language Models' Training? / 2401.11033 / ISBN:https://doi.org/10.48550/arXiv.2401.11033 / Published by ArXiv / on (web) Publishing site
- References
- Detecting Multimedia Generated by Large AI Models: A Survey / 2402.00045 / ISBN:https://doi.org/10.48550/arXiv.2402.00045 / Published by ArXiv / on (web) Publishing site
- 3 Detection
- User Modeling and User Profiling: A Comprehensive Survey / 2402.09660 / ISBN:https://doi.org/10.48550/arXiv.2402.09660 / Published by ArXiv / on (web) Publishing site
- 4 Current Taxonomy
- AGI Artificial General Intelligence for Education / 2304.12479 / ISBN:https://doi.org/10.48550/arXiv.2304.12479 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
- The Journey to Trustworthy AI- Part 1 Pursuit of Pragmatic Frameworks / 2403.15457 / ISBN:https://doi.org/10.48550/arXiv.2403.15457 / Published by ArXiv / on (web) Publishing site
- 2 Trustworthy AI Too Many Definitions or Lack Thereof?
- A Review of Multi-Modal Large Language and Vision Models / 2404.01322 / ISBN:https://doi.org/10.48550/arXiv.2404.01322 / Published by ArXiv / on (web) Publishing site
- 4 Specific Large Language Models
- AI Alignment: A Comprehensive Survey / 2310.19852 / ISBN:https://doi.org/10.48550/arXiv.2310.19852 / Published by ArXiv / on (web) Publishing site
- 2 Learning from Feedback
- Detecting AI Generated Text Based on NLP and Machine Learning Approaches / 2404.10032 / ISBN:https://doi.org/10.48550/arXiv.2404.10032 / Published by ArXiv / on (web) Publishing site
- II. Literature Review
- From Model Performance to Claim: How a Change of Focus in Machine Learning Replicability Can Help Bridge the Responsibility Gap / 2404.13131 / ISBN:https://doi.org/10.1145/3630106.3658951 / Published by ArXiv / on (web) Publishing site
- 2 Disentangling Replicability of Model Performance Claiim and Replicability of
Social Claim
- A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law / 2405.01769 / ISBN:https://doi.org/10.48550/arXiv.2405.01769 / Published by ArXiv / on (web) Publishing site
- 3 Finance
4 Medicine and Healthcare - A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs) / 2405.03066 / ISBN:https://doi.org/10.48550/arXiv.2405.03066 / Published by ArXiv / on (web) Publishing site
- 3 Results
- A Comprehensive Overview of Large Language Models (LLMs) for Cyber Defences: Opportunities and Directions / 2405.14487 / ISBN:https://doi.org/10.48550/arXiv.2405.14487 / Published by ArXiv / on (web) Publishing site
- VIII. Ethical LLMs
- How Ethical Should AI Be? How AI Alignment Shapes the Risk Preferences of LLMs / 2406.01168 / ISBN:https://doi.org/10.48550/arXiv.2406.01168 / Published by ArXiv / on (web) Publishing site
- Introduction
- Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health
/ 2406.13659 / ISBN:https://doi.org/10.48550/arXiv.2406.13659 / Published by ArXiv / on (web) Publishing site
- III. CASE STUDIES : APPLICATIONS OF LLM S IN PATIENT
ENGAGEMENT
- Have We Reached AGI? Comparing ChatGPT, Claude, and Gemini to Human Literacy and Education Benchmarks / 2407.09573 / ISBN:https://doi.org/10.48550/arXiv.2407.09573 / Published by ArXiv / on (web) Publishing site
- 4 Data Analysis and Results
- Deepfake Media Forensics: State of the Art and Challenges Ahead / 2408.00388 / ISBN:https://doi.org/10.48550/arXiv.2408.00388 / Published by ArXiv / on (web) Publishing site
- 4. Passive Deepfake Authentication Methods
- Between Copyright and Computer Science: The Law and Ethics of Generative AI / 2403.14653 / ISBN:https://doi.org/10.48550/arXiv.2403.14653 / Published by ArXiv / on (web) Publishing site
- I. The Why and How Behind LLMs
II. The Difference Between Academic and Commercial Research - VersusDebias: Universal Zero-Shot Debiasing for Text-to-Image Models via SLM-Based Prompt Engineering and Generative Adversary / 2407.19524 / ISBN:https://doi.org/10.48550/arXiv.2407.19524 / Published by ArXiv / on (web) Publishing site
- Abstract
I Introduction
4 Experiment
5 Limitation and Future Work
Appendices - Don't Kill the Baby: The Case for AI in Arbitration / 2408.11608 / ISBN:https://doi.org/10.48550/arXiv.2408.11608 / Published by ArXiv / on (web) Publishing site
- I. AI and the Federal Arbitration ACt
- CIPHER: Cybersecurity Intelligent Penetration-testing Helper for Ethical Researcher / 2408.11650 / ISBN:https://doi.org/10.48550/arXiv.2408.11650 / Published by ArXiv / on (web) Publishing site
- 4. Experiment Results
- Large language models as linguistic simulators and cognitive models in human research / 2402.04470 / ISBN:https://doi.org/10.48550/arXiv.2402.04470 / Published by ArXiv / on (web) Publishing site
- Six fallacies that misinterpret language models
- XTRUST: On the Multilingual Trustworthiness of Large Language Models / 2409.15762 / ISBN:https://doi.org/10.48550/arXiv.2409.15762 / Published by ArXiv / on (web) Publishing site
- 4 Experiments
- Clinnova Federated Learning Proof of Concept: Key Takeaways from a Cross-border Collaboration / 2410.02443 / ISBN:https://doi.org/10.48550/arXiv.2410.02443 / Published by ArXiv / on (web) Publishing site
- VII. Evaluations and Experiments
- Learning Human-like Representations to Enable Learning Human Values / 2312.14106 / ISBN:https://doi.org/10.48550/arXiv.2312.14106 / Published by ArXiv / on (web) Publishing site
- A. Appendix
- Navigating the Cultural Kaleidoscope: A Hitchhiker's Guide to Sensitivity in Large Language Models
/ 2410.12880 / ISBN:https://doi.org/10.48550/arXiv.2410.12880 / Published by ArXiv / on (web) Publishing site
- 8 Results after cultural safeguarding
- Towards Automated Penetration Testing: Introducing LLM Benchmark, Analysis, and Improvements / 2410.17141 / ISBN:https://doi.org/10.48550/arXiv.2410.17141 / Published by ArXiv / on (web) Publishing site
- 4 Evaluation
- The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships / 2410.20130 / ISBN:https://doi.org/10.48550/arXiv.2410.20130 / Published by ArXiv / on (web) Publishing site
- References
- Democratizing Reward Design for Personal and Representative Value-Alignment / 2410.22203 / ISBN:https://doi.org/10.48550/arXiv.2410.22203 / Published by ArXiv / on (web) Publishing site
- 7 Discussion
- Bias in Large Language Models: Origin, Evaluation, and Mitigation / 2411.10915 / ISBN:https://doi.org/10.48550/arXiv.2411.10915 / Published by ArXiv / on (web) Publishing site
- 4. Bias Evaluation
- Framework for developing and evaluating ethical collaboration between expert and machine / 2411.10983 / ISBN:https://doi.org/10.48550/arXiv.2411.10983 / Published by ArXiv / on (web) Publishing site
- References
- Can OpenAI o1 outperform humans in higher-order cognitive thinking? / 2412.05753 / ISBN:https://doi.org/10.48550/arXiv.2412.05753 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
5 Conclusion - Political-LLM: Large Language Models in Political Science / 2412.06864 / ISBN:https://doi.org/10.48550/arXiv.2412.06864 / Published by ArXiv / on (web) Publishing site
- 4 Classical Political Science Functions and Modern Transformations
References - Shaping AI's Impact on Billions of Lives / 2412.02730 / ISBN:https://doi.org/10.48550/arXiv.2412.02730 / Published by ArXiv / on (web) Publishing site
- I. Putting Pragmatic AI in Context
Bibliography - AI Ethics in Smart Homes: Progress, User Requirements and Challenges / 2412.09813 / ISBN:https://doi.org/10.48550/arXiv.2412.09813 / Published by ArXiv / on (web) Publishing site
- 5 AI Ethics from Technology's Perspective
- INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models / 2501.01973 / ISBN:https://doi.org/10.48550/arXiv.2501.01973 / Published by ArXiv / on (web) Publishing site
- 5 Experiments & Results
- Harnessing the Potential of Large Language Models in Modern Marketing Management: Applications, Future Directions, and Strategic Recommendations / 2501.10685 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- 6- Campaign Optimization and
Management
- Examining the Expanding Role of Synthetic Data Throughout the AI Development Pipeline / 2501.18493 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- References
- Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription / 2502.04356 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site
- III. State-of-the-Art in Open Healthcare LLMs and AIFMs
IV. Leveraging Open LLMs for Prescription: A Case Study - On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective / 2502.14296 / ISBN:https://doi.org/10.48550/arXiv.2502.14296 / Published by ArXiv / on (web) Publishing site
- 7 Benchmarking Vision-Language Models
References - Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review / 2502.14886 / ISBN:https://doi.org/10.48550/arXiv.2502.14886 / Published by ArXiv / on (web) Publishing site
- VI. Open Issues and Future Research Directions in Surgical Scene Understanding
- Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Models / 2502.18505 / ISBN:https://doi.org/10.48550/arXiv.2502.18505 / Published by ArXiv / on (web) Publishing site
- 3. Results
- Vision Language Models in Medicine / 2503.01863 / ISBN:https://doi.org/10.48550/arXiv.2503.01863 / Published by ArXiv / on (web) Publishing site
- III. Core Concepts of Visual Language Modeling
IV. VLM Benchmarking and Evaluations - Medical Hallucinations in Foundation Models and Their Impact on Healthcare / 2503.05777 / ISBN:https://doi.org/10.48550/arXiv.2503.05777 / Published by ArXiv / on (web) Publishing site
- 5 Mitigation Strategies
- LLMs in Disease Diagnosis: A Comparative Study of DeepSeek-R1 and O3 Mini Across Chronic Health Conditions
/ 2503.10486 / ISBN:https://doi.org/10.48550/arXiv.2503.10486 / Published by ArXiv / on (web) Publishing site
- 4 Results
5 Discussion - Policy Frameworks for Transparent Chain-of-Thought Reasoning in Large Language Models / 2503.14521 / ISBN:https://doi.org/10.48550/arXiv.2503.14521 / Published by ArXiv / on (web) Publishing site
- 3 Arguments pro Transparent CoT
- Towards Adaptive AI Governance: Comparative Insights from the U.S., EU, and Asia / 2504.00652 / ISBN:https://doi.org/10.48550/arXiv.2504.00652 / Published by ArXiv / on (web) Publishing site
- References