collaborators

51 papers

cs.AI2026

V-DEAL: Diagnosing Video Safety De-Calibration as an Understanding-Refusal Coupling Failure

Zhetong Zhang, Honghao Fu, Miao Xu +2

As Video Large Language Models are increasingly deployed in real-world applications, ensuring their safety alignment has become critical. Counterintuitively, we find that harmful v…

cs.CV2026

EchoFoley: Event-Centric Hierarchical Control for Video Grounded Creative Sound Generation

Bingxuan Li, Yiming Cui, Yicheng He +4

Sound effects build an essential layer of multimodal storytelling, shaping the emotional atmosphere and the narrative semantics of videos. Despite recent advancement in video-text-…

cs.CV2026

What Should a Streaming Video Model Remember?

Haonan Ge, Yiwei Wang, Hang Wu +1

Streaming video understanding models must answer queries at any moment during an ongoing stream, using only what they have observed so far and under fixed memory and computation bu…

cs.LG2026

Prune-OPD: Efficient and Reliable On-Policy Distillation for Long-Horizon Reasoning

Zhicheng Yang, Zhijiang Guo, Yifan Song +5

On-policy distillation (OPD) leverages dense teacher rewards to enhance reasoning models. However, scaling OPD to long-horizon tasks exposes a critical flaw: as the student's gener…

cs.CV2026

Semantic-Aware Adaptive Visual Memory for Streaming Video Understanding

Hang Wu, Sherin Mary Mathews, Yujun Cai +2

Online streaming video understanding requires models to process continuous visual inputs and respond to user queries in real time, where the unbounded stream and unpredictable quer…

cs.CV2026

Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment

Zhixue Song, Boyan Han, Yiwei Wang +1

Recent advancements in visual context compression enable MLLMs to process ultra-long contexts efficiently by rendering text into images. However, we identify a critical vulnerabili…