7 citations · 7 across the 10 of their papers we have counts for
6 papers · 1 filter
Visual Reasoning Tracer: Object-Level Grounded Reasoning Benchmark
Haobo Yuan, Yueyi Sun, Yanwei Li +7
Recent advances in Multimodal Large Language Models (MLLMs) have significantly improved performance on tasks such as visual grounding and visual question answering. However, the re…
MMaDA-Parallel: Multimodal Large Diffusion Language Models for Thinking-Aware Editing and Generation
Ye Tian, Ling Yang, Jiongfan Yang +10
While thinking-aware generation aims to improve performance on complex tasks, we identify a critical failure mode where existing sequential, autoregressive approaches can paradoxic…
PairUni: Pairwise Training for Unified Multimodal Language Models
Jiani Zheng, Zhiyang Teng, Kunpeng Qiu +6
Unified Vision-Language Models (UVLMs) perform both understanding and generation within a single architecture. Since these models rely on heterogeneous data and supervision, balanc…
Open-o3-Video: Grounded Video Reasoning with Explicit Spatio-Temporal Evidence
Jiahao Meng, Xiangtai Li, Haochen Wang +8
Most video reasoning models only generate textual reasoning traces without indicating when and where key evidence appears. Recent models such as OpenAI-o3 have sparked wide interes…
Grasp Any Region: Towards Precise, Contextual Pixel Understanding for Multimodal LLMs
Haochen Wang, Yuhao Wang, Tao Zhang +13
While Multimodal Large Language Models (MLLMs) excel at holistic understanding, they struggle in capturing the dense world with complex scenes, requiring fine-grained analysis of i…
Traceable Evidence Enhanced Visual Grounded Reasoning: Evaluation and Methodology
Haochen Wang, Xiangtai Li, Zilong Huang +9
Models like OpenAI-o3 pioneer visual grounded reasoning by dynamically referencing visual regions, just like human "thinking with images". However, no benchmark exists to evaluate…