Tag: Robustness

All the articles with the tag "Robustness".

• 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.

• Purity Law for Generalizable Neural TSP Solvers

  Published: 15 May, 2025 |  at  11:09 AM

  

  98.11 🤔

  This paper introduces Purity Law (PuLa), a structural principle revealing sparsity bias in optimal TSP solutions, and proposes Purity Policy Optimization (PUPO), a training framework that significantly enhances the generalization of neural TSP solvers across diverse scales and distributions without inference overhead.

• 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.

• A Large-Scale Empirical Analysis of Custom GPTs' Vulnerabilities in the OpenAI Ecosystem

  Published: 16 May, 2025 |  at  11:13 AM

  

  94.41 🤔

  This paper conducts a large-scale empirical analysis of 14,904 custom GPTs in the OpenAI store, revealing over 95% lack adequate security against attacks like roleplay (96.51%) and phishing (91.22%), introduces a multi-metric popularity ranking system, and highlights the need for enhanced security in both custom and base models.