activity
20232026
collaborators

8 papers

cs.CL2026

Detect Before You Disambiguate: Perturbation-Based Input Ambiguity Detection in LLMs

Tiejin Chen, Xiaoou Liu, Michael Clifford +5

Large language models (LLMs) often answer ambiguous inputs as if they had a single intended meaning. This is problematic because input ambiguity is an upstream source of uncertaint…

cs.CV2026

STRIDE: Evaluating Spatiotemporal Reasoning in Driving Edge Cases

Lieqi Liu, Rui gao, Jia-Chen Gu +6

In autonomous driving, perceiving surrounding objects is not enough: failing to understand how they move and interact over time can lead to dangerous decisions. Evaluating vision-l…

cs.RO2026

Directional Pullback Regularization for Long-Horizon Rollout of Latent World Models in Autonomous Driving

Shatadal Mishra, Ahmadreza Moradipari, Nejib Ammar

Learned world models for autonomous driving operate in unconstrained latent spaces, yet the physical systems they represent are governed by strict non-holonomic constraints: ground…

cs.RO2026

Network-Efficient World Model Token Streaming

Shatadal Mishra, Ahmadreza Moradipari, Nejib Ammar

Generative driving world models rely on compact latent state representations that must be efficiently transmitted and synchronized across distributed compute and connected vehicles…

cs.AI2026

Agentic AI for Trip Planning Optimization Application

Tiejin Chen, Ahmadreza Moradipari, Kyungtae Han +2

Trip planning for intelligent vehicles increasingly requires selecting optimal routes rather than merely producing feasible itineraries, as interacting factors such as travel time,…

cs.RO2025

IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-Tuning

Dechen Gao, Hang Wang, Hanchu Zhou +5

Imitation learning (IL) and reinforcement learning (RL) each offer distinct advantages for robotics policy learning: IL provides stable learning from demonstrations, and RL promote…

eess.SY2024

Tolerance of Reinforcement Learning Controllers against Deviations in Cyber Physical Systems

Changjian Zhang, Parv Kapoor, Eunsuk Kang +5

Cyber-physical systems (CPS) with reinforcement learning (RL)-based controllers are increasingly being deployed in complex physical environments such as autonomous vehicles, the In…

eess.SY2023

Investigating Robustness in Cyber-Physical Systems: Specification-Centric Analysis in the face of System Deviations

Changjian Zhang, Parv Kapoor, Romulo Meira-Goes +5

The adoption of cyber-physical systems (CPS) is on the rise in complex physical environments, encompassing domains such as autonomous vehicles, the Internet of Things (IoT), and sm…