activity
20242026
collaborators

13 papers

cs.CV2026

Uncovering and Shaping the Latent Representation of 3D Scene Topology in Vision-Language Models

Haoming Wang, Wei Gao

Decades of cognitive science establish that humans navigate environments by forming cognitive maps, defined as allocentric and topology-preserving representations of 3D space. Whil…

cs.CV2026

MosaicThinker: On-Device Visual Spatial Reasoning for Embodied AI via Iterative Construction of Space Representation

Haoming Wang, Qiyao Xue, Weichen Liu +1

When embodied AI is expanding from traditional object detection and recognition to more advanced tasks of robot manipulation and actuation planning, visual spatial reasoning from t…

cs.CV2025

InfiniBench: Infinite Benchmarking for Visual Spatial Reasoning with Customizable Scene Complexity

Haoming Wang, Qiyao Xue, Wei Gao

Modern vision-language models (VLMs) are expected to have abilities of spatial reasoning with diverse scene complexities, but evaluating such abilities is difficult due to the lack…

cs.AI2025

Reasoning Path and Latent State Analysis for Multi-view Visual Spatial Reasoning: A Cognitive Science Perspective

Qiyao Xue, Weichen Liu, Shiqi Wang +3

Spatial reasoning is a core aspect of human intelligence that allows perception, inference and planning in 3D environments. However, current vision-language models (VLMs) struggle…

cs.AI2025

Spatial Reasoning in Multimodal Large Language Models: A Survey of Tasks, Benchmarks and Methods

Weichen Liu, Qiyao Xue, Haoming Wang +3

Spatial reasoning, which requires ability to perceive and manipulate spatial relationships in the 3D world, is a fundamental aspect of human intelligence, yet remains a persistent…

cs.LG2025

Deciphering Personalization: Towards Fine-Grained Explainability in Natural Language for Personalized Image Generation Models

Haoming Wang, Wei Gao

Image generation models are usually personalized in practical uses in order to better meet the individual users' heterogeneous needs, but most personalized models lack explainabili…