18 citations · 30 across the 9 of their papers we have counts for
10 papers
Kimi K3: Open Frontier Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +398
We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…
GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models
5 Team, Aohan Zeng, Xin Lv +167
We present GLM-4.5, an open-source Mixture-of-Experts (MoE) large language model with 355B total parameters and 32B activated parameters, featuring a hybrid reasoning method that s…
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…
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…
AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models
Yuhang Wu, Wenmeng Yu, Yean Cheng +5
Evaluating the alignment capabilities of large Vision-Language Models (VLMs) is essential for determining their effectiveness as helpful assistants. However, existing benchmarks pr…
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…
Colorizing Monochromatic Radiance Fields
Yean Cheng, Renjie Wan, Shuchen Weng +3
Though Neural Radiance Fields (NeRF) can produce colorful 3D representations of the world by using a set of 2D images, such ability becomes non-existent when only monochromatic ima…