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

16 citations · 57 across the 22 of their papers we have counts for

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Showing 2025Show all

10 papers · 1 filter

astro-ph.IM2025★ 1 cited

AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy

Jinghang Shi, Xiaoyu Tang, Yang Huang +4

Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…

cs.CL2025

Sequential Diffusion Language Models

Yangzhou Liu, Yue Cao, Hao Li +13

Diffusion language models (DLMs) have strong theoretical efficiency but are limited by fixed-length decoding and incompatibility with key-value (KV) caches. Block diffusion mitigat…

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★ 1 cited

MMBench-GUI: Hierarchical Multi-Platform Evaluation Framework for GUI Agents

Xuehui Wang, Zhenyu Wu, JingJing Xie +25

We introduce MMBench-GUI, a hierarchical benchmark for evaluating GUI automation agents across Windows, macOS, Linux, iOS, Android, and Web platforms. It comprises four levels: GUI…

cs.CV2025

Docopilot: Improving Multimodal Models for Document-Level Understanding

Yuchen Duan, Zhe Chen, Yusong Hu +9

Despite significant progress in multimodal large language models (MLLMs), their performance on complex, multi-page document comprehension remains inadequate, largely due to the lac…

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

Visual Embodied Brain: Let Multimodal Large Language Models See, Think, and Control in Spaces

Gen Luo, Ganlin Yang, Ziyang Gong +15

The remarkable progress of Multimodal Large Language Models (MLLMs) has attracted increasing attention to extend them to physical entities like legged robot. This typically require…

cs.CV2025

VisuLogic: A Benchmark for Evaluating Visual Reasoning in Multi-modal Large Language Models

Weiye Xu, Jiahao Wang, Weiyun Wang +10

Visual reasoning is a core component of human intelligence and a critical capability for advanced multimodal models. Yet current reasoning evaluations of multimodal large language…

cs.CV2025★ 8 cited

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models

Jinguo Zhu, Weiyun Wang, Zhe Chen +48

We introduce InternVL3, a significant advancement in the InternVL series featuring a native multimodal pre-training paradigm. Rather than adapting a text-only large language model…

cs.CV2025

VisualPRM: An Effective Process Reward Model for Multimodal Reasoning

Weiyun Wang, Zhangwei Gao, Lianjie Chen +12

We introduce VisualPRM, an advanced multimodal Process Reward Model (PRM) with 8B parameters, which improves the reasoning abilities of existing Multimodal Large Language Models (M…