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Enhancing Social Robots through Resilient AI

arXiv 2510.21469 ↗First posted 24 Oct 2025cs.RO cs.AIcited by 0

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Abstract (arXiv)

As artificial intelligence continues to advance and becomes more integrated into sensitive areas like healthcare, education, and everyday life, it's crucial for these systems to be both resilient and robust. This paper shows how resilience is a fundamental characteristic of social robots, which, through it, ensure trust in the robot itself-an essential element especially when operating in contexts with elderly people, who often have low trust in these systems. Resilience is therefore the ability to operate under adverse or stressful conditions, even when degraded or weakened, while maintaining essential operational capabilities.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 27 references that are in the map. First posted on arXiv 24 Oct 2025.

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References · 8

  1. 2021Measure and Improve Robustness in NLP Models: A Surveycited by 107
  2. 2024Exploring Vulnerabilities and Protections in Large Language Models: A Surveycited by 10
  3. 2022Robust Natural Language Processing: Recent Advances, Challenges, and Future Directionscited by 9
  4. 2023Security Considerations in AI-Robotics: A Survey of Current Methods, Challenges, and Opportunitiescited by 9
  5. 2021RAILS: A Robust Adversarial Immune-inspired Learning Systemcited by 8
  6. 2024Cooperative Resilience in Artificial Intelligence Multiagent Systemscited by 8
  7. 2024Disentangling Uncertainty for Safe Social Navigation using Deep Reinforcement Learningcited by 2
  8. 2022Resilient robot teams: a review integrating decentralised control, change-detection, and learningcited by 1

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