From the 1 of 7 linked papers with an AI index.
7 papers
High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving
Muhammad Ayub Sabir, Junbiao Pang, Fatima Ashraf
Accurate Global Navigation Satellite System (GNSS)-based localization is essential for safe and reliable autonomous driving. However, spoofing attacks can manipulate vehicle positi…
Large Multimodal Agents for Intelligent Transportation Systems: Architectures, Evidence, and Deployment Challenges
Muhammad Ayub Sabir, Shaohong Zheng, Zhiyu Qu +2
Large multimodal agents (LMAs) are increasingly proposed for intelligent transportation systems (ITS), but existing studies often conflate multimodality, agency, empirical performa…
Artificial Intelligence for Understanding and Managing Transportation Behavior in Sustainable Smart Cities
Junbiao Pang, Muhammad Ayub Sabir, Fatima Ashraf
Urban transportation systems generate heterogeneous data, yet these data do not automatically become actionable management intelligence. This chapter adopts a behavior-centered per…
Efficient Tuning Before Low-Bit Post-Training Quantization for Stochastic Gradient Descent-optimized Models
Peng Xia, Junbiao Pang, Muhammad Ayub Sabir
The paper introduces Efficient Tuning Before Quantization (ETBQ), a lightweight pre‑conditioning step that adjusts a full‑precision model using perturbations from quantization erro…
Discovering Sparse Counterfactual Factors via Latent Adjustment for Survey-based Community Intervention
Fatima Ashraf, Muhammad Ayub Sabir, Junbiao Pang +2
Transportation surveys are widely used to understand travel preferences and adoption barriers, yet most survey-based analyses remain descriptive or predictive and rarely provide sp…
Importance-aware Topic Modeling for Discovering Public Transit Risk from Noisy Social Media
Fatima Ashraf, Muhammad Ayub Sabir, Jiaxin Deng +2
Urban transit agencies increasingly turn to social media to monitor emerging service risks such as crowding, delays, and safety incidents, yet the signals of concern are sparse, sh…