5 papers
Naju: A Native Discrete State-Space Model with Independent Retention and Writing for Long-Sequence Memory
Hyuk Lim, Seunghyun Yoon
Long-sequence memory tracking places two opposing demands on a recurrent state: near-lossless retention of stored bindings over long horizons, and active overwriting of stale ones.…
DriveMind: A Dual Visual Language Model-based Reinforcement Learning Framework for Autonomous Driving
Dawood Wasif, Terrence J. Moore, Chandan K. Reddy +5
End-to-end autonomous driving systems map sensor data directly to control commands, but remain opaque, lack interpretability, and offer no formal safety guarantees. While recent vi…
Risk-Aware Human-in-the-Loop Framework with Adaptive Intrusion Response for Autonomous Vehicles
Dawood Wasif, Terrence J. Moore, Seunghyun Yoon +4
Autonomous vehicles must remain safe and effective when encountering rare long-tailed scenarios or cyber-physical intrusions during driving. We present RAIL, a risk-aware human-in-…
DASH: Deception-Augmented Shared Mental Model for a Human-Machine Teaming System
Zelin Wan, Han Jun Yoon, Nithin Alluru +6
We present DASH (Deception-Augmented Shared mental model for Human-machine teaming), a novel framework that enhances mission resilience by embedding proactive deception into Shared…
Advancing Human-Machine Teaming: Concepts, Challenges, and Applications
Dian Chen, Han Jun Yoon, Zelin Wan +9
Human-Machine Teaming (HMT) is revolutionizing collaboration across domains such as defense, healthcare, and autonomous systems by integrating AI-driven decision-making, trust cali…