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Bingjie Gao

3 accepted papers

2026

Breaking Dual Bottlenecks: Evolving Unified Multimodal Models into Self-Adaptive Interleaved Visual Reasoners

ICML 2026poster

Recent unified models integrate multimodal understanding and generation within a single framework. However, an ``understanding-generation gap'' persists, where models can capture user intent but often fail to translate this semantic knowledge into precise pixel-level manipulation. This gap results i…

Cited by 0SourceScholar
2026

CineTrans: Learning to Generate Videos with Cinematic Transitions via Masked Diffusion Models

ICLR 2026poster

Despite significant advances in video synthesis, research into multi-shot video generation remains in its infancy. Even with scaled-up models and massive datasets, the shot transition capabilities remain rudimentary and unstable, largely confining generated videos to single-shot sequences. In this w…

Cited by 0SourcecodeScholar
2025

The Devil is in the Prompts: Retrieval-Augmented Prompt Optimization for Text-to-Video Generation

CVPR 2025poster

The evolution of Text-to-video (T2V) generative models, trained on large-scale datasets, has been marked by significant progress. However, the sensitivity of T2V generative models to input prompts highlights the critical role of prompt design in influencing generative outcomes. Prior research has pr…