activity
20242026
collaborators

7 papers

cs.AI2026

SpatialWorld: Benchmarking Interactive Spatial Reasoning of Multimodal Agents in Real-World Tasks

Hongcheng Gao, Hailong Qu, Jingyi Tang +18

Spatial reasoning is a foundational capability for multimodal large language models (MLLMs) to perceive and operate within the physical world. However, existing benchmarks predomin…

cs.GR2026

JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation

Lin Song, Wenbo Li, Guoqing Ma +16

We present JoyAI-Image, a unified multimodal foundation model for visual understanding, text-to-image generation, and instruction-guided image editing. JoyAI-Image couples a spatia…

cs.CV2026

Thinking with Novel Views: A Systematic Analysis of Generative-Augmented Spatial Intelligence

Yanbing Zhang, Bo Wang, Jianhui Liu +9

Current Large Multimodal Models (LMMs) struggle with spatial reasoning tasks requiring viewpoint-dependent understanding, largely because they are confined to a single, static obse…

cs.CL2026

TextLDM: Language Modeling with Continuous Latent Diffusion

Jiaxiu Jiang, Jingjing Ren, Wenbo Li +10

Diffusion Transformers (DiT) trained with flow matching in a VAE latent space have unified visual generation across images and videos. A natural next step toward a single architect…

cs.LG2025

MC#: Mixture Compressor for Mixture-of-Experts Large Models

Wei Huang, Yue Liao, Yukang Chen +6

Mixture-of-Experts (MoE) effectively scales large language models (LLMs) and vision-language models (VLMs) by increasing capacity through sparse activation. However, preloading all…

cs.LG2025

Mixture Compressor for Mixture-of-Experts LLMs Gains More

Wei Huang, Yue Liao, Jianhui Liu +6

Mixture-of-Experts large language models (MoE-LLMs) marks a significant step forward of language models, however, they encounter two critical challenges in practice: 1) expert para…