8 papers
Stable-MM-R1: Anchoring Multimodal Reasoning Dynamics via Entropy-Guided Stratification
Yimeng Ye, Shuang Chen, Wenxuan Huang +8
While Reinforcement Learning (RL) effectively incentivizes reasoning in Large Language Models, current pipelines are hindered by training instability and rapid entropy collapse. Th…
Flow-OPD: On-Policy Distillation for Flow Matching Models
Zhen Fang, Wenxuan Huang, Yu Zeng +8
Existing Flow Matching (FM) text-to-image models suffer from two critical bottlenecks under multi-task alignment: the reward sparsity induced by scalar-valued rewards, and the grad…
4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding
Zhangquan Chen, Manyuan Zhang, Xinlei Yu +9
Dynamic spatial reasoning from monocular video is essential for bridging visual intelligence and the physical world, yet remains challenging for vision-language models (VLMs). Prio…
OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents
Shuang Chen, Kaituo Feng, Hangting Chen +7
Deep search has become a crucial capability for frontier multimodal agents, enabling models to solve complex questions through active search, evidence verification, and multi-step…
Unify-Agent: A Unified Multimodal Agent for World-Grounded Image Synthesis
Shuang Chen, Quanxin Shou, Hangting Chen +16
Unified multimodal models provide a natural and promising architecture for understanding diverse and complex real-world knowledge while generating high-quality images. However, the…
Gen-Searcher: Reinforcing Agentic Search for Image Generation
Kaituo Feng, Manyuan Zhang, Shuang Chen +7
Recent image generation models have shown strong capabilities in generating high-fidelity and photorealistic images. However, they are fundamentally constrained by frozen internal…
Exploring Reasoning Reward Model for Agents
Kaixuan Fan, Kaituo Feng, Manyuan Zhang +7
Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However, most methods still relies on sparse…
OneThinker: All-in-one Reasoning Model for Image and Video
Kaituo Feng, Manyuan Zhang, Hongyu Li +11
Reinforcement learning (RL) has recently achieved remarkable success in eliciting visual reasoning within Multimodal Large Language Models (MLLMs). However, existing approaches typ…