14 citations · 15 across the 6 of their papers we have counts for
6 papers
Scaling Spatial Reasoning in MLLMs through Programmatic Data Synthesis
Zhi Helu, Huang Jingjing, Xu Wang +9
Embodied intelligence, a grand challenge in artificial intelligence, is fundamentally constrained by the limited spatial understanding and reasoning capabilities of current models.…
Bridging Traditional Machine Learning and Large Language Models: A Two-Part Course Design for Modern AI Education
Fang Li
This paper presents an innovative pedagogical approach for teaching artificial intelligence and data science that systematically bridges traditional machine learning techniques wit…
The Immutable Tensor Architecture: A Pure Dataflow Approach for Secure, Energy-Efficient AI Inference
Fang Li
The deployment of Large Language Models (LLMs) on consumer edge devices is throttled by the "Memory Wall" -- the prohibitive bandwidth and energy cost of fetching gigabytes of mode…
Kimi K2: Open Agentic Intelligence
Kimi Team, Yifan Bai, Yiping Bao +195
We introduce Kimi K2, a Mixture-of-Experts (MoE) large language model with 32 billion activated parameters and 1 trillion total parameters. We propose the MuonClip optimizer, which…
Jigsaw-Puzzles: From Seeing to Understanding to Reasoning in Vision-Language Models
Zesen Lyu, Dandan Zhang, Wei Ye +3
Spatial reasoning is a core component of human cognition, enabling individuals to perceive, comprehend, and interact with the physical world. It relies on a nuanced understanding o…
Kimi-VL Technical Report
Kimi Team, Angang Du, Bohong Yin +92
We present Kimi-VL, an efficient open-source Mixture-of-Experts (MoE) vision-language model (VLM) that offers advanced multimodal reasoning, long-context understanding, and strong…