collaborators

9 papers

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

A Large-Scale Multimodal Dataset and Benchmarks for Human Activity Scene Understanding and Reasoning

Siyang Jiang, Mu Yuan, Xiang Ji +12

Multimodal human action recognition (HAR) leverages complementary sensors for activity classification. Beyond recognition, recent advances in large language models (LLMs) enable de…

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…