49 citations · 75 across the 8 of their papers we have counts for
10 papers
GroundingPI: A Grounding Foundation Model towards Physical Intelligence with Visual Primitives
Qize Yu, Lianrui Fan, Boyu Chen +23
Precise grounding matters. It specifies which object is the target and where that object is, even in clutter and for tiny objects, and it has to be fast enough for closed-loop cont…
VistaGEN: Consistent Driving Video Generation with Fine-Grained Control Using Multiview Visual-Language Reasoning
Li-Heng Chen, Ke Cheng, Yahui Liu +3
Driving video generation has achieved much progress in controllability, video resolution, and length, but fails to support fine-grained object-level controllability for diverse dri…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
V Team, Wenyi Hong, Wenmeng Yu +90
We present GLM-4.1V-Thinking, GLM-4.5V, and GLM-4.6V, a family of vision-language models (VLMs) designed to advance general-purpose multimodal understanding and reasoning. In this…
MotionBench: Benchmarking and Improving Fine-grained Video Motion Understanding for Vision Language Models
Wenyi Hong, Yean Cheng, Zhuoyi Yang +6
In recent years, vision language models (VLMs) have made significant advancements in video understanding. However, a crucial capability - fine-grained motion comprehension - remain…
VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation
Jiazheng Xu, Yu Huang, Jiale Cheng +19
Visual generative models have achieved remarkable progress in synthesizing photorealistic images and videos, yet aligning their outputs with human preferences across critical dimen…
DreamPolish: Domain Score Distillation With Progressive Geometry Generation
Yean Cheng, Ziqi Cai, Ming Ding +5
We introduce DreamPolish, a text-to-3D generation model that excels in producing refined geometry and high-quality textures. In the geometry construction phase, our approach levera…
CogVLM2: Visual Language Models for Image and Video Understanding
Wenyi Hong, Weihan Wang, Ming Ding +22
Beginning with VisualGLM and CogVLM, we are continuously exploring VLMs in pursuit of enhanced vision-language fusion, efficient higher-resolution architecture, and broader modalit…
CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
Zhuoyi Yang, Jiayan Teng, Wendi Zheng +15
We present CogVideoX, a large-scale text-to-video generation model based on diffusion transformer, which can generate 10-second continuous videos aligned with text prompt, with a f…
LVBench: An Extreme Long Video Understanding Benchmark
Weihan Wang, Zehai He, Wenyi Hong +9
Recent progress in multimodal large language models has markedly enhanced the understanding of short videos (typically under one minute), and several evaluation datasets have emerg…