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20242026
most citedPOINTS1.5: Building a Vision-Language Model towards Real World Applications

1 citations · 1 across the 7 of their papers we have counts for

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cs.CV2026

POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs

Haicheng Wang, Yuan Liu, Yikun Liu +9

Multimodal Large Language Models (MLLMs) have recently demonstrated remarkable capabilities in cross-modal understanding and generation. However, the rapid growth of visual token s…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…

cs.CV20241 cited

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…