6 papers
Latent World Models with Monotone Planning Costs for Image-Goal Navigation
Amirhosein Chahe, Siwei Cai, Lifeng Zhou
Image-goal navigation with latent world models requires not only accurate future prediction, but also a planning cost that reliably ranks candidate action sequences. We define the…
What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models
Amirhosein Chahe, Tyler Naes, Jovin D'sa +4
Autonomous vehicles must safely navigate complex environments where planning-critical agents may be hidden from view. Current approaches often treat all occlusions with uniform con…
Policy-Guided World Model Planning for Language-Conditioned Visual Navigation
Amirhosein Chahe, Lifeng Zhou
Navigating to a visually specified goal given natural language instructions remains a fundamental challenge in embodied AI. Existing approaches either rely on reactive policies tha…
ReasonDrive: Efficient Visual Question Answering for Autonomous Vehicles with Reasoning-Enhanced Small Vision-Language Models
Amirhosein Chahe, Lifeng Zhou
Vision-language models (VLMs) show promise for autonomous driving but often lack transparent reasoning capabilities that are critical for safety. We investigate whether explicitly…
Query3D: LLM-Powered Open-Vocabulary Scene Segmentation with Language Embedded 3D Gaussian
Amirhosein Chahe, Lifeng Zhou
This paper introduces a novel method for open-vocabulary 3D scene querying in autonomous driving by combining Language Embedded 3D Gaussians with Large Language Models (LLMs). We p…
Dynamic Adversarial Attacks on Autonomous Driving Systems
Amirhosein Chahe, Chenan Wang, Abhishek Jeyapratap +2
This paper introduces an attacking mechanism to challenge the resilience of autonomous driving systems. Specifically, we manipulate the decision-making processes of an autonomous v…