30 papers
VA-Judger: Reward Modeling from Human Preference Feedback for Joint Video-Audio Generation
Yinming Huang, Shuyuan Tu, Xi Yan +5
Using reinforcement learning to post-train joint video-audio generation models requires a reward signal. Existing methods construct this reward by combining metrics for individual…
4D-WAM: 4D Consistent World Modeling for Autonomous Driving
Jiacheng Fu, Yibo Yuan, Meng Tian +8
Emerging World-Action Models (WAMs) have demonstrated promising performance in autonomous driving by jointly modeling future driving scene evolution and trajectory planning. Howeve…
SUV: Future Scene Understanding as Video Generation for End-to-End Driving
Yibo Yuan, Jiacheng Fu, Jiangtong Zhu +8
End-to-end driving requires a coherent understanding of future scenes, yet existing methods model these scenes using task-specific heads and output formats, with limited scalabilit…
WAM-Diff2: Hierarchical AR-to-Diffusion Distillation for Highly Efficient Autonomous Driving VLA
Zhihao Zhu, Hanlin Shang, Mingwang Xu +6
Vision-Language-Action (VLA) models have emerged as a prominent paradigm for end-to-end autonomous driving; however, their efficient deployment is severely constrained by high comp…
Beyond the Eye: Efficient Multimodal Reasoning via Self-Regulated Implicit Visual Tools
Xiuwei Chen, Quanlin Chen, Wentao Hu +8
The paper introduces Beyond the Eye (BEE), an implicit visual‑tool framework for multimodal large language models that learns to self‑regulate when to invoke visual tools, reducing…
SyncLoop: A Multimodal Dual-Loop Framework for Self-Improving Mathematical Reasoning
Xiuwei Chen, Wentao Hu, Hanhui Li +9
Recent advances in multimodal large language models (MLLMs) have shown impressive reasoning capabilities. However, further enhancing existing MLLMs necessitates high-quality vision…