5 papers
MAIN-VLA: Modeling Abstraction of Intention and eNvironment for Vision-Language-Action Models
Zheyuan Zhou, Liang Du, Zixun Sun +5
Despite significant progress in Visual-Language-Action (VLA), in highly complex and dynamic environments that involve real-time unpredictable interactions (such as 3D open worlds a…
OccLE: Label-Efficient 3D Semantic Occupancy Prediction
Naiyu Fang, Zheyuan Zhou, Fayao Liu +5
3D semantic occupancy prediction offers an intuitive and efficient scene understanding and has attracted significant interest in autonomous driving perception. Existing approaches…
DSOcc: Leveraging Depth Awareness and Semantic Aid to Boost Camera-Based 3D Semantic Occupancy Prediction
Naiyu Fang, Zheyuan Zhou, Kang Wang +5
Camera-based 3D semantic occupancy prediction offers an efficient and cost-effective solution for perceiving surrounding scenes in autonomous driving. However, existing works rely…
CAE: Character-Level Autoencoder for Non-Semantic Relational Data Grouping
Veera V S Bhargav Nunna, Shinae Kang, Zheyuan Zhou +3
Enterprise relational databases increasingly contain vast amounts of non-semantic data - IP addresses, product identifiers, encoded keys, and timestamps - that challenge traditiona…
CAD-Judge: Toward Efficient Morphological Grading and Verification for Text-to-CAD Generation
Zheyuan Zhou, Jiayi Han, Liang Du +3
Computer-Aided Design (CAD) models are widely used across industrial design, simulation, and manufacturing processes. Text-to-CAD systems aim to generate editable, general-purpose…