1 citations · 2 across the 8 of their papers we have counts for
9 papers
Foresight: Iterative Reasoning About Clues that Matter for Navigation
Arthur Zhang, Carl Qi, Donne Su +3
Open-world mapless navigation from sparse language instructions requires resolving underspecified goals and inferring which environmental cues are relevant for reaching the goal. F…
AI-Assisted Peer Review at Scale: The AAAI-26 AI Review Pilot
Joydeep Biswas, Sheila Schoepp, Gautham Vasan +10
Scientific peer review faces mounting strain as submission volumes surge, making it increasingly difficult to sustain review quality, consistency, and timeliness. Recent advances i…
VENTURA: Adapting Image Diffusion Models for Unified Task Conditioned Navigation
Arthur Zhang, Xiangyun Meng, Luca Calliari +5
Robots must adapt to diverse human instructions and operate safely in unstructured, open-world environments. Recent Vision-Language models (VLMs) offer strong priors for grounding…
CREStE: Scalable Mapless Navigation with Internet Scale Priors and Counterfactual Guidance
Arthur Zhang, Harshit Sikchi, Amy Zhang +1
We introduce CREStE, a scalable learning-based mapless navigation framework to address the open-world generalization and robustness challenges of outdoor urban navigation. Key to a…
Lift, Splat, Map: Lifting Foundation Masks for Label-Free Semantic Scene Completion
Arthur Zhang, Rainier Heijne, Joydeep Biswas
Autonomous mobile robots deployed in urban environments must be context-aware, i.e., able to distinguish between different semantic entities, and robust to occlusions. Current appr…
Looking Inside Out: Anticipating Driver Intent From Videos
Yung-chi Kung, Arthur Zhang, Junmin Wang +1
Anticipating driver intention is an important task when vehicles of mixed and varying levels of human/machine autonomy share roadways. Driver intention can be leveraged to improve…
Towards Robust Robot 3D Perception in Urban Environments: The UT Campus Object Dataset
Arthur Zhang, Chaitanya Eranki, Christina Zhang +8
We introduce the UT Campus Object Dataset (CODa), a mobile robot egocentric perception dataset collected on the University of Texas Austin Campus. Our dataset contains 8.5 hours of…
Convolutional Bayesian Kernel Inference for 3D Semantic Mapping
Joey Wilson, Yuewei Fu, Arthur Zhang +5
Robotic perception is currently at a cross-roads between modern methods, which operate in an efficient latent space, and classical methods, which are mathematically founded and pro…
MotionSC: Data Set and Network for Real-Time Semantic Mapping in Dynamic Environments
Joey Wilson, Jingyu Song, Yuewei Fu +5
This work addresses a gap in semantic scene completion (SSC) data by creating a novel outdoor data set with accurate and complete dynamic scenes. Our data set is formed from random…