2 citations · 2 across the 9 of their papers we have counts for
11 papers
VAMR: Multi-Question Agentic Reasoning for Efficient Long-Form Video Understanding
Runquan Gui, Hanzhu Chen, Zehao Wang +3
Long-form video understanding often involves multiple questions about different aspects of the same recording. Yet existing video agents typically process each question through an…
PhysVista: Benchmarking Physical Intelligence in VLMs via a Perception-Reasoning-Assessment Loop
Xinge Peng, Yiting Lu, Tianwu Zhi +4
Vision-Language Models (VLMs) have shown strong multimodal reasoning capabilities, yet whether they truly capture the physical consistency underlying real-world dynamics remains un…
CoT-Edit: Let CoT Guide Instruction Video Editing
Sen Liang, Fengbin Guan, Youliang Zhang +2
Text-driven instruction-based video editing in complex scenes remains challenging: purely textual prompts often fail to capture precise spatial relationships and physical constrain…
Goku: A Million-Scale Universal Dataset and Benchmark for Instruction-Based Video Editing
Sen Liang, Cong Wang, Zhentao Yu +8
Existing instruction-based video editing datasets commonly focus on single-task appearance editing, failing to meet the complex creative demands of real-world scenarios. To bridge…
SpongeBob: Sync-Aware Harmonious Audio-Visual Generative Editing
Sen Liang, Cong Wang, Fengbin Guan +6
Visual and acoustic events in the physical world are inherently coupled, yet existing video editing methods typically adopt decoupled pipelines, lacking bidirectional modality inte…
MACReD: A Multi-Agent Collaborative Reasoning Framework for Reaction Diagram Parsing
Chuang Tang, Chenhao Lin, Yin Xu +5
Parsing chemical reaction diagrams from scientific literature is challenging due to heterogeneous layouts, intertwined visual elements, and the difficulty of integrating recognitio…
Mags-RL: Wearing Multimodal LLMs a Magnifying Glass via Agentic Reinforcement Learning For Complex Scene Reasoning
Xuanzhao Dong, Wenhui Zhu, Peijie Qiu +11
Despite their popularity and success, Multimodal Large Language Models (MLLMs) often struggle to interpret images accurately, which limits their reasoning capability in complex sce…
OphIn-500K: Curating Web-Scale Visual Instructions for Scaling Ophthalmic Multimodal Large Language Models
Xuanzhao Dong, Wenhui Zhu, Xiwen Chen +13
The advancement of general medical Multimodal Large Language Models (MLLMs) has shown great potential for building conversational assistants to support clinical diagnosis. However,…
IQA-Spider: Unifying Multi-Granularity Image Quality Assessment with Reasoning, Grounding and Referring
Xinge Peng, Yiting Lu, Xin Li +1
We present IQA-Spider, the first image quality assessment (IQA) framework that unifies reasoning, grounding, and referring into a single LMM-based framework for multi-granularity q…
PromptEnhancer: A Simple Approach to Enhance Text-to-Image Models via Chain-of-Thought Prompt Rewriting
Linqing Wang, Ximing Xing, Yiji Cheng +13
Recent advancements in text-to-image (T2I) diffusion models have demonstrated remarkable capabilities in generating high-fidelity images. However, these models often struggle to fa…
OmniV2V: Versatile Video Generation and Editing via Dynamic Content Manipulation
Sen Liang, Zhentao Yu, Zhengguang Zhou +8
The emergence of Diffusion Transformers (DiT) has brought significant advancements to video generation, especially in text-to-video and image-to-video tasks. Although video generat…