collaborators

7 papers

cs.CL2026

Can AI Reason Like an Urban Planner? Benchmarking Large Language Models Against Professional Judgment

Yijie Deng, He Zhu, Wen Wang +3

Problem, Research Strategy, and Findings: The rise of large language models (LLMs) raises a key question for urban planning: which forms of professional planning knowledge can AI r…

cs.CL2026

PlanBench-V: A Spatial Planning Map Benchmark for Vision-Language Models

Minxin Chen, He Zhu, Junyou Su +3

Spatial planning maps are central to territorial governance, translating planning objectives, regulations, and spatial strategies into visual forms for decision-making, public comm…

cs.RO2026

AnyImageNav: Any-View Geometry for Precise Last-Meter Image-Goal Navigation

Yijie Deng, Shuaihang Yuan, Yi Fang

Image Goal Navigation (ImageNav) is evaluated by a coarse success criterion, the agent must stop within 1m of the target, which is sufficient for finding objects but falls short fo…

cs.IR2025

SilverTorch: A Unified Model-based System to Democratize Large-Scale Recommendation on GPUs

Bi Xue, Hong Wu, Lei Chen +29

Serving deep learning based recommendation models (DLRM) at scale is challenging. Existing approaches rely on dedicated ANN indexing and filtering services on CPUs, suffering from…

cs.RO2025

FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling

Yijie Deng, Shuaihang Yuan, Congcong Wen +4

Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot navigation. Existing approaches either…

cs.CV2025

Hierarchical Scoring with 3D Gaussian Splatting for Instance Image-Goal Navigation

Yijie Deng, Shuaihang Yuan, Geeta Chandra Raju Bethala +3

Instance Image-Goal Navigation (IIN) requires autonomous agents to identify and navigate to a target object or location depicted in a reference image captured from any viewpoint. W…

cs.CL2025

PlanGPT-VL: Enhancing Urban Planning with Domain-Specific Vision-Language Models

He Zhu, Junyou Su, Minxin Chen +4

In the field of urban planning, existing Vision-Language Models (VLMs) frequently fail to effectively analyze and evaluate planning maps, despite the critical importance of these v…