collaborators

7 papers

cs.AI2026

How Do LLMs and VLMs Understand Viewpoint Rotation Without Vision? An Interpretability Study

Zhen Yang, Ping Jian, Zhongbin Guo +5

Over the past year, spatial intelligence has drawn increasing attention. Many prior works study it from the perspective of visual-spatial intelligence, where models have access to…

cs.MM2026

Look, Listen and Segment: Towards Weakly Supervised Audio-visual Semantic Segmentation

Chengzhi Li, Heyan Huang, Ping Jian +1

Audio-Visual Semantic Segmentation (AVSS) aligns audio and video at the pixel level but requires costly per-frame annotations. We introduce Weakly Supervised Audio-Visual Semantic…

cs.CV2026

Understanding Temporal Logic Consistency in Video-Language Models through Cross-Modal Attention Discriminability

Chengzhi Li, Heyan Huang, Ping Jian +3

Large language models (LLMs) often generate self-contradictory outputs, which severely impacts their reliability and hinders their adoption in practical applications. In video-lang…

cs.AI2026

The Struggle Between Continuation and Refusal: A Mechanistic Analysis of the Continuation-Triggered Jailbreak in LLMs

Yonghong Deng, Zhen Yang, Ping Jian +3

With the rapid advancement of large language models (LLMs), the safety of LLMs has become a critical concern. Despite significant efforts in safety alignment, current LLMs remain v…

cs.CV2026

TAMMs: Change Understanding and Forecasting in Satellite Image Time Series with Temporal-Aware Multimodal Models

Zhongbin Guo, Yuhao Wang, Ping Jian +4

Temporal Change Description (TCD) and Future Satellite Image Forecasting (FSIF) are critical, yet historically disjointed tasks in Satellite Image Time Series (SITS) analysis. Both…

cs.CV2026

Can LLMs See Without Pixels? Benchmarking Spatial Intelligence from Textual Descriptions

Zhongbin Guo, Zhen Yang, Yushan Li +6

Recent advancements in Spatial Intelligence (SI) have predominantly relied on Vision-Language Models (VLMs), yet a critical question remains: does spatial understanding originate f…