collaborators

9 papers

cs.CV2026

OmniCoT: A Benchmark for Global and Multi-Step Panoramic Reasoning

Haocong He, Chenfei Liao, Zichen Wen +13

Multimodal Large Language Models (MLLMs) have demonstrated promising spatial reasoning capabilities, while these abilities remain underexplored in the emerging visual modality of p…

cs.CL2026

Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs

Yubo Gao, Haotian Wu, Hong Chen +8

Chain-of-Thought (CoT) has significantly enhanced LLM reasoning, yet often incurs substantial computational overhead due to "overthinking": generating excessively long rationales w…

cs.CV2026

CM-EVS: Sparse Panoramic RGB-D-Pose Data for Complete Scene Coverage

Jiale Liu, Jungang Li, Jieming Yu +13

Modern 3D visual learning relies on observations sampled from metric 3D assets, yet existing scans, meshes, point clouds, simulations, and reconstructions do not directly provide a…

cs.CV2026

AndroTMem: From Interaction Trajectories to Anchored Memory in Long-Horizon GUI Agents

Yibo Shi, Jungang Li, Linghao Zhang +25

Long-horizon GUI agents are a key step toward real-world deployment, yet effective interaction memory under prevailing paradigms remains under-explored. Replaying full interaction…

cs.CV2026

Temporal Gains, Spatial Costs: Revisiting Video Fine-Tuning in Multimodal Large Language Models

Linghao Zhang, Jungang Li, Yonghua Hei +12

Multimodal large language models (MLLMs) are typically trained in multiple stages, with video-based supervised fine-tuning (Video-SFT) serving as a key step for improving visual un…

cs.CV2025

Multimodal Spatial Reasoning in the Large Model Era: A Survey and Benchmarks

Xu Zheng, Zihao Dongfang, Lutao Jiang +17

Humans possess spatial reasoning abilities that enable them to understand spaces through multimodal observations, such as vision and sound. Large multimodal reasoning models extend…