4 papers
ARise: Towards Knowledge-Augmented Reasoning via Risk-Adaptive Search
Yize Zhang, Tianshu Wang, Sirui Chen +6
Large language models (LLMs) have demonstrated impressive capabilities and are receiving increasing attention to enhance their reasoning through scaling test--time compute. However…
GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning
Chengqi Duan, Rongyao Fang, Yuqing Wang +5
Visual generation models have made remarkable progress in creating realistic images from text prompts, yet struggle with complex prompts that specify multiple objects with precise…
GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and Editing
Rongyao Fang, Chengqi Duan, Kun Wang +9
Current image generation and editing methods primarily process textual prompts as direct inputs without reasoning about visual composition and explicit operations. We present Gener…
PUMA: Empowering Unified MLLM with Multi-granular Visual Generation
Rongyao Fang, Chengqi Duan, Kun Wang +7
Recent advancements in multimodal foundation models have yielded significant progress in vision-language understanding. Initial attempts have also explored the potential of multimo…