mlsanityData to 7 Oct 2026

Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey

arXiv 2406.05392 ↗First posted 8 Jun 2024cs.CL cs.AI cs.CYcited by 23

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Abstract (arXiv)

Large Language Models (LLMs) have achieved unparalleled success across diverse language modeling tasks in recent years. However, this progress has also intensified ethical concerns, impacting the deployment of LLMs in everyday contexts. This paper provides a comprehensive survey of ethical challenges associated with LLMs, from longstanding issues such as copyright infringement, systematic bias, and data privacy, to emerging problems like truthfulness and social norms. We critically analyze existing research aimed at understanding, examining, and mitigating these ethical risks. Our survey underscores integrating ethical standards and societal values into the development of LLMs, thereby guiding the development of responsible and ethically aligned language models.

Key facts. Cited by 23 papers in the map (data through 7 Oct 2026). Builds on 247 of its 370 references that are in the map. First posted on arXiv 8 Jun 2024.

Builds on

247 of 370 references.

References · 247

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 7; 2025: 12; 2026: 4.

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  1. 2025Large Language Model Agent: A Survey on Methodology, Applications and Challengescited by 194
  2. 2024Sycophancy in Large Language Models: Causes and Mitigationscited by 97
  3. 2024The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harmcited by 67
  4. 2024Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language Modelscited by 28
  5. 2024UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Modelscited by 18
  6. 2025A Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomycited by 9
  7. 2024Blockchain for Large Language Model Security and Safety: A Holistic Surveycited by 8
  8. 2024Video Watermarking: Safeguarding Your Video from (Unauthorized) Annotations by Video-based LLMscited by 7
  9. 2025Reasoning Is Not All You Need: Examining LLMs for Multi-Turn Mental Health Conversationscited by 6
  10. 2025Protecting Your Video Content: Disrupting Automated Video-based LLM Annotationscited by 5
  11. 2025Towards Alignment-Centric Paradigm: A Survey of Instruction Tuning in Large Language Modelscited by 5
  12. 2025Breaking the Loop: Detecting and Mitigating Denial-of-Service Vulnerabilities in Large Language Modelscited by 3
11 more
  1. 2025Domain Specific Benchmarks for Evaluating Multimodal Large Language Modelscited by 2
  2. 2025Ethical Concerns of Generative AI and Mitigation Strategies: A Systematic Mapping Studycited by 1
  3. 2025Supernova Event Dataset: Interpreting Large Language Models' Personality through Critical Event Analysiscited by 1
  4. 2026The Hidden Cost of Contextual Sycophancy: an AI Literacy Intervention in Human-AI Collaborationcited by 1
  5. 2024Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical groundcited by 0
  6. 2025Generative KI f"ur TAcited by 0
  7. 2025EPT Benchmark: Evaluation of Persian Trustworthiness in Large Language Modelscited by 0
  8. 2025Plausibility as Failure: How LLMs and Humans Co-Construct Epistemic Errorcited by 0
  9. 2026Rules or Weights? Comparing User Understanding of Explainable AI Techniques with the Cognitive XAI-Adaptive Modelcited by 0
  10. 2026Adversarial Moral Stress Testing of Large Language Modelscited by 0
  11. 2026Backdoor Learning in Language Models and Vision-Language Modelscited by 0

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  1. 2024A Survey on the Honesty of Large Language Models
  2. 2024MoralBench: Moral Evaluation of LLMs
  3. 2024Fortifying Ethical Boundaries in AI: Advanced Strategies for Enhancing Security in Large Language Models
  4. 2025Towards Ethical Multi-Agent Systems of Large Language Models: A Mechanistic Interpretability Perspective
  5. 2025Mapping Trustworthiness in Large Language Models: A Bibliometric Analysis Bridging Theory to Practice
  6. 2024LocalValueBench: A Collaboratively Built and Extensible Benchmark for Evaluating Localized Value Alignment and Ethical Safety in Large Language Models
  7. 2025SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation
  8. 2025Diverse Human Value Alignment for Large Language Models via Ethical Reasoning