15 citations · 40 across the 20 of their papers we have counts for
5 papers · 1 filter
Thinking by Doing: Building Efficient World Model Reasoning in LLMs via Multi-turn Interaction
Bao Shu, Yan Cai, Jianjian Sun +11
Developing robust world model reasoning is crucial for large language model (LLM) agents to plan and interact in complex environments. While multi-turn interaction offers a superio…
Open Vision Reasoner: Transferring Linguistic Cognitive Behavior for Visual Reasoning
Yana Wei, Liang Zhao, Jianjian Sun +15
The remarkable reasoning capability of large language models (LLMs) stems from cognitive behaviors that emerge through reinforcement with verifiable rewards. This work investigates…
DGAE: Diffusion-Guided Autoencoder for Efficient Latent Representation Learning
Dongxu Liu, Jiahui Zhu, Yuang Peng +6
Autoencoders empower state-of-the-art image and video generative models by compressing pixels into a latent space through visual tokenization. Although recent advances have allevia…
Perception-R1: Pioneering Perception Policy with Reinforcement Learning
En Yu, Kangheng Lin, Liang Zhao +11
Inspired by the success of DeepSeek-R1, we explore the potential of rule-based reinforcement learning (RL) in MLLM post-training for perception policy learning. While promising, ou…
Step1X-Edit: A Practical Framework for General Image Editing
Shiyu Liu, Yucheng Han, Peng Xing +21
In recent years, image editing models have witnessed remarkable and rapid development. The recent unveiling of cutting-edge multimodal models such as GPT-4o and Gemini2 Flash has i…