9 papers
CRISP: Pre-LLM Yet Text-Driven Visual Token Pruning for Efficient LVLM Inference
Xu Li, Yi Zheng, Mengyang Zhao +7
Large Vision-Language Models (LVLMs) typically require processing hundreds to thousands of visual tokens, leading to substantial inference overhead. Existing visual token pruning m…
DocCogito: Aligning Layout Cognition and Step-Level Grounded Reasoning for Document Understanding
Yuchuan Wu, Minghan Zhuo, Teng Fu +3
Document understanding with multimodal large language models (MLLMs) requires not only accurate answers but also explicit, evidence-grounded reasoning, especially in high-stakes sc…
OmniPT: Unleashing the Potential of Large Vision Language Models for Pedestrian Tracking and Understanding
Teng Fu, Mengyang Zhao, Ke Niu +2
LVLMs have been shown to perform excellently in image-level tasks such as VQA and caption. However, in many instance-level tasks, such as visual grounding and object detection, LVL…
CReFT-CAD: Boosting Orthographic Projection Reasoning for CAD via Reinforcement Fine-Tuning
Ke Niu, Zhuofan Chen, Haiyang Yu +5
Computer-Aided Design (CAD) plays a pivotal role in industrial manufacturing. Orthographic projection reasoning underpins the entire CAD workflow, encompassing design, manufacturin…
From Intent to Execution: Multimodal Chain-of-Thought Reinforcement Learning for Precise CAD Code Generation
Ke Niu, Haiyang Yu, Zhuofan Chen +4
Computer-Aided Design (CAD) plays a vital role in engineering and manufacturing, yet current CAD workflows require extensive domain expertise and manual modeling effort. Recent adv…
Interpretable Oracle Bone Script Decipherment through Radical and Pictographic Analysis with LVLMs
Kaixin Peng, Mengyang Zhao, Haiyang Yu +2
As the oldest mature writing system, Oracle Bone Script (OBS) has long posed significant challenges for archaeological decipherment due to its rarity, abstractness, and pictographi…