collaborators

14 papers

cs.CV2026

SemComp-Bench: Benchmarking Semantic Task Completion in Video Generation

Keyu Tu, Zhuowei Chen, Mengqi Huang +4

We introduce Semantic Task Completion Video Generation, an outcome-oriented video generation task. Under this formulation, success requires both achievement of the intended outcome…

cs.CV2026

Lance: Unified Multimodal Modeling by Multi-Task Synergy

Fengyi Fu, Mengqi Huang, Shaojin Wu +10

We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather than relying on model capacity…

cs.CV2026

CLAP: Contrastive Latent-space Prompt Optimization for End-to-end Autonomous Driving

Ruiyang Zhu, Yuehan He, Boyuan Zheng +4

End-to-end autonomous driving systems powered by Vision-Language-Action (VLA) models achieve strong performance on common driving scenarios, yet remain brittle in rare but safety-c…

cs.CV2026

Stream-T1: Test-Time Scaling for Streaming Video Generation

Yijing Tu, Shaojin Wu, Mengqi Huang +4

While Test-Time Scaling (TTS) offers a promising direction to enhance video generation without the surging costs of training, current test-time video generation methods based on di…

cs.CV2026

Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation

Bin Wu, Mengqi Huang, Shaojin Wu +4

Distillation-based acceleration has become foundational for making autoregressive streaming video diffusion models practical, with distribution matching distillation (DMD) as the d…

cs.CV2026

NativeTok: Native Visual Tokenization for Improved Image Generation

Bin Wu, Mengqi Huang, Weinan Jia +1

VQ-based image generation typically follows a two-stage pipeline: a tokenizer encodes images into discrete tokens, and a generative model learns their dependencies for reconstructi…