190 citations · 247 across the 13 of their papers we have counts for
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cs.LG2024★ 3 cited
LLaMA-Mesh: Unifying 3D Mesh Generation with Language Models
Zhengyi Wang, Jonathan Lorraine, Yikai Wang +4
This work explores expanding the capabilities of large language models (LLMs) pretrained on text to generate 3D meshes within a unified model. This offers key advantages of (1) lev…
cs.LG2023
ATT3D: Amortized Text-to-3D Object Synthesis
Jonathan Lorraine, Kevin Xie, Xiaohui Zeng +7
Text-to-3D modelling has seen exciting progress by combining generative text-to-image models with image-to-3D methods like Neural Radiance Fields. DreamFusion recently achieved hig…
cs.LG2023★ 2 cited
To transfer or not transfer: Unified transferability metric and analysis
Qianshan Zhan, Xiao-Jun Zeng
In transfer learning, transferability is one of the most fundamental problems, which aims to evaluate the effectiveness of arbitrary transfer tasks. Existing research focuses on cl…