4 citations · 4 across the 10 of their papers we have counts for
14 papers
FilmFlow: Agentic System for 3D Virtual Film Cinematography
Yiming Zhang, Jiarui Guo, Haojia Wei +5
Complex camera motion is central to visual storytelling, yet translating cinematographic intent into controllable, executable camera trajectories remains challenging. We introduce…
DeSpatial: The devil of Agentic Spatial Reasoning Lies in 3D Itself
Yifei Liu, Xiaolong Zhou, Ziyang Gong +8
Spatial agents have access to reconstruction and segmentation tools, yet inconsistent predictions and fragmented object identities can prevent their outputs from becoming reliable…
MetaReason: Precise Interleaved Multimodal Reasoning via Editing Meta Information for Solving Geometry Problems
Penghao Yin, Haomin Wang, Qihong Tang +3
Although visual reasoning is crucial for solving complex geometry tasks, existing vision-language models rely heavily on text-only reasoning. Some recent methods introduce intermed…
Intern-S2-Preview: Scientific Agentic Foundation Model
Lei Bai, Jiaqi Cao, Chiyu Chen +121
Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sus…
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…
SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation
Xiaolong Zhou, Yifei Liu, Ziyang Gong +8
Multimodal Large Language Models (MLLMs) have made rapid progress in spatial intelligence, yet existing spatial reasoning benchmarks largely assume pristine visual inputs and overl…
PhotoFlow: Agentic 3D Virtual Photography Missions
Jiarui Guo, Haojia Wei, Yiming Zhang +5
Virtual photography asks an agent to enter a prepared 3D scene with no preselected camera pose or reference image, infer a suitable shot from scene information and a language inten…
Reliable Reasoning in SVG-LLMs via Multi-Task Multi-Reward Reinforcement Learning
Haomin Wang, Qi Wei, Qianli Ma +4
With the rapid advancement of vision-language models, an increasing number of studies have explored their potential for SVG generation tasks. Although existing approaches improve p…
InternVL-U: Democratizing Unified Multimodal Models for Understanding, Reasoning, Generation and Editing
Changyao Tian, Danni Yang, Guanzhou Chen +26
Unified multimodal models (UMMs) that integrate understanding, reasoning, generation, and editing face inherent trade-offs between maintaining strong semantic comprehension and acq…
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…
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…
Intern-S1: A Scientific Multimodal Foundation Model
Lei Bai, Zhongrui Cai, Yuhang Cao +173
In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…
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…
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…