1 citations · 1 across the 11 of their papers we have counts for
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TIIF-Bench: How Does Your T2I Model Follow Your Instructions?
Xinyu Wei, Jinrui Zhang, Zeqing Wang +4
The rapid advancements of Text-to-Image (T2I) models have ushered in a new phase of AI-generated content, marked by their growing ability to interpret and follow user instructions.…
SpatialFlow-GRPO: Where Spatial Credit Drives Image Editing
Yankai Yang, Yancheng Long, Wei Chen +7
Recent online reinforcement learning has substantially improved image editing quality. However, existing Flow-GRPO-style methods usually rely on a single whole-image reward, which…
Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation
Zihan Su, Hongyang Wei, Kangrui Cen +4
Unified Multimodal Models (UMMs) integrate both visual understanding and generation within a single framework. Their ultimate aspiration is to create a cycle where understanding an…
VideoVerse: Does Your T2V Generator Have World Model Capability to Synthesize Videos?
Zeqing Wang, Xinyu Wei, Bairui Li +5
The recent rapid advancement of Text-to-Video (T2V) generation technologies are engaging the trained models with more world model ability, making the existing benchmarks increasing…
SpatialReward: Bridging the Perception Gap in Online RL for Image Editing via Explicit Spatial Reasoning
Yancheng Long, Yankai Yang, Hongyang Wei +12
Online Reinforcement Learning (RL) offers a promising avenue for complex image editing but is currently constrained by the scarcity of reliable and fine-grained reward signals. Exi…
MICo-150K: A Comprehensive Dataset Advancing Multi-Image Composition
Xinyu Wei, Kangrui Cen, Hongyang Wei +6
In controllable image generation, synthesizing coherent and consistent images from multiple reference inputs, i.e., Multi-Image Composition (MICo), remains a challenging problem, p…