7 papers
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…
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…
The Struggle Between Continuation and Refusal: A Mechanistic Analysis of the Continuation-Triggered Jailbreak in LLMs
Yonghong Deng, Zhen Yang, Ping Jian +4
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…
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…
LISA-3D: Lifting Language-Image Segmentation to 3D via Multi-View Consistency
Zhongbin Guo, Jiahe Liu, Wenyu Gao +4
Text-driven 3D reconstruction requires masks that understand free-form instructions and remain stable under viewpoint changes. We present LISA-3D, a two-stage framework that adapts…
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…
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…