10 papers
ReasonUni: Reasoning-Augmented Reconstruction Advances Unified Multimodal Models
Feize Wu, Zhiyuan Yan, Yuhuan Hong +10
Image-to-text (I2T) understanding and text-to-image (T2I) generation are dual tasks in unified multimodal models (UMMs). Reconstructive post-training couples these tasks, but exist…
UniSpace: Unified Visual Representation and Scalable Multimodal Modeling
Jinbo Yan, Limeng Qiao, Jie Qin +3
Semantic vision encoders have become a central visual interface for multimodal understanding and semantic conditioning in image generation. However, their final tokens discard fine…
MT-Web2Code: Benchmarking Coding Agents on Multi-Turn Regional Reconstruction and Localized Modification
Qiming Li, Shujie Hu, Haohan Liu +3
Recent advances in Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities in web UI generation. However, existing benchmarks predominantly focus on single-t…
HoloCount: A Holistic Visual Counting Benchmark for MLLMs
Jinhong Deng, Limeng Qiao, Guanglu Wan
Visual counting is a fundamental pillar of multimodal intelligence, requiring a seamless integration of fine-grained grounding and spatial reasoning. While Multimodal Large Languag…
X2SAM: Any Segmentation in Images and Videos
Hao Wang, Limeng Qiao, Chi Zhang +4
Multimodal Large Language Models (MLLMs) have demonstrated strong image-level visual understanding and reasoning, yet their pixel-level perception across both images and videos rem…
GeoAlign: Geometric Feature Realignment for MLLM Spatial Reasoning
Zhaochen Liu, Limeng Qiao, Guanglu Wan +1
Multimodal large language models (MLLMs) have exhibited remarkable performance in various visual tasks, yet still struggle with spatial reasoning. Recent efforts mitigate this by i…
MobileDreamer: Generative Sketch World Model for GUI Agent
Yilin Cao, Yufeng Zhong, Zhixiong Zeng +6
Mobile GUI agents have shown strong potential in real-world automation and practical applications. However, most existing agents remain reactive, making decisions mainly from curre…
MMDuet2: Enhancing Proactive Interaction of Video MLLMs with Multi-Turn Reinforcement Learning
Yueqian Wang, Songxiang Liu, Disong Wang +4
Recent advances in video multimodal large language models (Video MLLMs) have significantly enhanced video understanding and multi-modal interaction capabilities. While most existin…
Omni-AutoThink: Adaptive Multimodal Reasoning via Reinforcement Learning
Dongchao Yang, Songxiang Liu, Disong Wang +3
Recent advances in Omni models have enabled unified multimodal perception and generation. However, most existing systems still exhibit rigid reasoning behaviors, either overthinkin…
UniComp: Rethinking Video Compression Through Informational Uniqueness
Chao Yuan, Shimin Chen, Minliang Lin +3
Distinct from attention-based compression methods, this paper presents an information uniqueness driven video compression framework, termed UniComp, which aims to maximize the info…