5 citations · 5 across the 4 of their papers we have counts for
5 papers
Making MLLM Latents Matter: Factor-Aware Predictive Learning for Cinematic Video Generation
Songlin Yang, Zhe Wang, Xiaotong Zhao +8
Cinematic video generation requires both temporal inference from limited inputs (i.e., sparse rather than frame-by-frame guidance) and factor-aware control of character, scene, act…
OmniVBench: A Benchmark and Large-Scale Dataset for Omni Reference-to-Video Generation
Wenxue Li, Peiyan Guan, Haoyang Jiang +15
Omni reference-to-video (R2V) generation is emerging as a general paradigm that enables flexible video customization from diverse and compositional visual references. However, exis…
CogOmniControl: Reasoning-Driven Controllable Video Generation via Creative Intent Cognition
Hongji Yang, Songlian Li, Yucheng Zhou +4
Recent diffusion models achieve strong photorealism and fluency in video generation, yet remain fragile under abstract, sparse or complex conditions, leading to poor performance in…
HanMoVLM: Large Vision-Language Models for Professional Artistic Painting Evaluation
Hongji Yang, Yucheng Zhou, Wencheng Han +3
While Large Vision-Language Models (VLMs) demonstrate impressive general visual capabilities, they remain artistically blind and unable to offer professional evaluation of artworks…
LangGPT: Rethinking Structured Reusable Prompt Design Framework for LLMs from the Programming Language
Ming Wang, Yuanzhong Liu, Xiaoyu Liang +11
LLMs have demonstrated commendable performance across diverse domains. Nevertheless, formulating high-quality prompts to instruct LLMs proficiently poses a challenge for non-AI exp…