2 citations · 3 across the 13 of their papers we have counts for
11 papers · 1 filter
DiffSpot: Can VLMs Spot Fine-Grained Visual Differences in Web Interfaces?
Linhao Zhang, Aiwei Liu, Yuan Liu +1
Vision-language models (VLMs) have made strong progress on high-level image-text alignment, yet their ability to perceive subtle visual differences remains limited. We study this p…
POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management
Yikun Liu, Yuan Liu, Haicheng Wang +6
Large Multimodal Models (LMMs) excel at visual perception but struggle with real-time, knowledge-intensive queries due to their reliance on static parametric knowledge. While multi…
VersaViT: Enhancing MLLM Vision Backbones via Task-Guided Optimization
Yikun Liu, Yuan Liu, Shangzhe Di +8
Multimodal Large Language Models (MLLMs) have recently achieved remarkable success in visual-language understanding, demonstrating superior high-level semantic alignment within the…
POINTS-GUI-G: GUI-Grounding Journey
Zhongyin Zhao, Yuan Liu, Yikun Liu +7
The rapid advancement of vision-language models has catalyzed the emergence of GUI agents, which hold immense potential for automating complex tasks, from online shopping to flight…
FinMMDocR: Benchmarking Financial Multimodal Reasoning with Scenario Awareness, Document Understanding, and Multi-Step Computation
Zichen Tang, Haihong E, Rongjin Li +18
We introduce FinMMDocR, a novel bilingual multimodal benchmark for evaluating multimodal large language models (MLLMs) on real-world financial numerical reasoning. Compared to exis…
Zero-Training Task-Specific Model Synthesis for Few-Shot Medical Image Classification
Yao Qin, Yangyang Yan, YuanChao Yang +4
Deep learning models have achieved remarkable success in medical image analysis but are fundamentally constrained by the requirement for large-scale, meticulously annotated dataset…
Patch-as-Decodable-Token: Towards Unified Multi-Modal Vision Tasks in MLLMs
Yongyi Su, Haojie Zhang, Shijie Li +11
Multimodal large language models (MLLMs) have advanced rapidly in recent years. However, existing approaches for vision tasks often rely on indirect representations, such as genera…
POINTS-Reader: Distillation-Free Adaptation of Vision-Language Models for Document Conversion
Yuan Liu, Zhongyin Zhao, Le Tian +8
High-quality labeled data is essential for training accurate document conversion models, particularly in domains with complex formats such as tables, formulas, and multi-column tex…
POINTS1.5: Building a Vision-Language Model towards Real World Applications
Yuan Liu, Le Tian, Xiao Zhou +4
Vision-language models have made significant strides recently, demonstrating superior performance across a range of tasks, e.g. optical character recognition and complex diagram an…
POINTS: Improving Your Vision-language Model with Affordable Strategies
Yuan Liu, Zhongyin Zhao, Ziyuan Zhuang +3
In recent years, vision-language models have made significant strides, excelling in tasks like optical character recognition and geometric problem-solving. However, several critica…
Rethinking Overlooked Aspects in Vision-Language Models
Yuan Liu, Le Tian, Xiao Zhou +1
Recent advancements in large vision-language models (LVLMs), such as GPT4-V and LLaVA, have been substantial. LLaVA's modular architecture, in particular, offers a blend of simplic…