5 papers
Understanding the Challenges in Iterative Generative Optimization with LLMs
Allen Nie, Xavier Daull, Zhiyi Kuang +10
Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using execution feedback. It is a promising approach…
CamLit: Unified Video Diffusion with Explicit Camera and Lighting Control
Zhiyi Kuang, Chengan He, Egor Zakharov +6
We present CamLit, the first unified video diffusion model that jointly performs novel view synthesis (NVS) and relighting from a single input image. Given one reference image, a u…
Learning Game-Playing Agents with Generative Code Optimization
Zhiyi Kuang, Ryan Rong, YuCheng Yuan +1
We present a generative optimization approach for learning game-playing agents, where policies are represented as Python programs and refined using large language models (LLMs). Ou…
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models
Zhiqiu Lin, Samuel Yu, Zhiyi Kuang +2
The ability to quickly learn a new task with minimal instruction - known as few-shot learning - is a central aspect of intelligent agents. Classical few-shot benchmarks make use of…
MonoHair: High-Fidelity Hair Modeling from a Monocular Video
Keyu Wu, Lingchen Yang, Zhiyi Kuang +6
Undoubtedly, high-fidelity 3D hair is crucial for achieving realism, artistic expression, and immersion in computer graphics. While existing 3D hair modeling methods have achieved…