8 papers · 1 filter
ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning
Yuan Zhao, Youwei Pang, Jiaming Zuo +10
Recent progress in promptable segmentation has shifted visual perception from object-level localization toward concept-level understanding. However, the notion of a concept remains…
PixVerve: Advancing Native UHR Image Generation to 100MP with a Large-Scale High-Quality Dataset
Haojun Chen, Haoyang He, Chengming Xu +11
Text-to-Image (T2I) models have recently seen notable progress around 1K and 2K resolution. With the extreme desire for better visual experience and the rapid development of imagin…
SPIKE: An Adaptive Dual Controller Framework for Cost-Efficient Long-Horizon Game Agents
Wencan Jiang, Jiangning Zhang, Jianbiao Mei +6
Long-horizon multimodal agents in open-world games must stay goal-directed across many low-level interactions under tight token and latency budgets. Existing approaches often trade…
Who Generated This 3D Asset? Learning Source Attribution for Generative 3D Models
Sihan Ma, Siyuan Liang, Dacheng Tao
Generative 3D models are deployed in gaming, robotics, and immersive creation, making source attribution critical: given a 3D asset, can we identify whether and which generative mo…
Learn to Think: Improving Multimodal Reasoning through Vision-Aware Self-Improvement Training
Qihuang Zhong, Liang Ding, Wenjie Xuan +3
Post-training with explicit reasoning traces is common to improve the reasoning capabilities of Multimodal Large Language Models (MLLMs). However, acquiring high-quality reasoning…
Multi-Domain Learning with Global Expert Mapping
Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou +3
Human perception generalizes well across different domains, but most vision models struggle beyond their training data. This gap motivates multi-dataset learning, where a single mo…
VideoTIR: Accurate Understanding for Long Videos with Efficient Tool-Integrated Reasoning
Zhe Gao, Shiyu Shen, Taifeng Chai +7
Existing Multimodal Large Language Models (MLLMs) often suffer from hallucinations in long video understanding (LVU), primarily due to the imbalance between textual and visual toke…
UniICL: Systematizing Unified Multimodal In-context Learning through a Capability-Oriented Taxonomy
Yicheng Xu, Jiangning Zhang, Zhucun Xue +5
In-context learning (ICL) enables fast task adaptation from demonstrations without per-task parameter updates but remains highly sensitive to example selection and formatting. In u…