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20242026
most citedExpanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

16 citations · 28 across the 11 of their papers we have counts for

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cs.CV2026

ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs

Yang Yang, Qinyu Zhao, Mouxiang Chen +5

Existing scaling strategies for Multimodal Large Language Models (MLLMs) typically expand either model parameters or sequential inference computation, incurring substantial memory…

cs.CV2026

COHERENCE: Benchmarking Fine-Grained Image-Text Alignment in Interleaved Multimodal Contexts

Bingli Wang, Huanze Tang, Haijun Lv +5

In recent years, Multimodal Large Language Models (MLLMs) have achieved remarkable progress on a wide range of multimodal benchmarks. Despite these advances, most existing benchmar…

cs.CV2025

InternSVG: Towards Unified SVG Tasks with Multimodal Large Language Models

Haomin Wang, Jinhui Yin, Qi Wei +12

General SVG modeling remains challenging due to fragmented datasets, limited transferability of methods across tasks, and the difficulty of handling structural complexity. In respo…

cs.CV2025★ 4 cited

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Weiyun Wang, Zhangwei Gao, Lixin Gu +72

We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…

cs.CV2025

InternSpatial: A Comprehensive Dataset for Spatial Reasoning in Vision-Language Models

Nianchen Deng, Lixin Gu, Shenglong Ye +17

Recent benchmarks and datasets have been proposed to improve spatial reasoning in vision-language models (VLMs), yet existing open resources remain limited in scale, visual diversi…

cs.CV2025

Point or Line? Using Line-based Representation for Panoptic Symbol Spotting in CAD Drawings

Xingguang Wei, Haomin Wang, Shenglong Ye +7

We study the task of panoptic symbol spotting, which involves identifying both individual instances of countable things and the semantic regions of uncountable stuff in computer-ai…