Tag: Human-AI Interaction

All the articles with the tag "Human-AI Interaction".

• AI in Money Matters

  Published: 15 May, 2025 |  at  11:03 AM

  

  99.13 🤔

  This paper investigates the cautious adoption of Large Language Models like ChatGPT in the Fintech industry through qualitative interviews, highlighting professionals' optimism for routine task automation, concerns over regulatory inadequacies, and interest in bespoke models to ensure compliance and data control.

• A Statistical Case Against Empirical Human-AI Alignment

  Published: 15 May, 2025 |  at  11:06 AM

  

  98.37 🤔

  This position paper argues against forward empirical human-AI alignment due to statistical biases and anthropocentric limitations, advocating for prescriptive and backward alignment approaches to ensure transparency and minimize bias, supported by a case study on language model decoding strategies.

• Belief Injection for Epistemic Control in Linguistic State Space

  Published: 16 May, 2025 |  at  11:37 AM

  

  96.91 🤔

  This paper proposes belief injection as a proactive epistemic control mechanism to shape AI agents' internal linguistic belief states within the Semantic Manifold framework, offering diverse strategies for guiding reasoning and alignment, though it lacks empirical validation.

• Thermal Detection of People with Mobility Restrictions for Barrier Reduction at Traffic Lights Controlled Intersections

  Published: 15 May, 2025 |  at  11:04 AM

  

  96.91 🤔

  This paper introduces a thermal detector-based traffic light system using YOLO-Thermal, a modified YOLOv8 framework, to dynamically adjust signal timings for individuals with mobility restrictions, achieving superior detection accuracy (89.1% APval) and enhancing intersection accessibility while addressing privacy and adverse condition challenges.

• Adversarial Attacks in Multimodal Systems: A Practitioner's Survey

  Published: 8 May, 2025 |  at  11:09 AM

  

  96.71 🤔

  This survey paper provides a comprehensive overview of adversarial attacks on multimodal AI systems across text, image, video, and audio modalities, categorizing threats by attacker knowledge, intention, and execution to equip practitioners with knowledge of vulnerabilities and cross-modal risks.