4 citations · 10 across the 7 of their papers we have counts for
7 papers
A foundation model enpowered by a multi-modal prompt engine for universal seismic geobody interpretation across surveys
Hang Gao, Xinming Wu, Luming Liang +4
Seismic geobody interpretation is crucial for structural geology studies and various engineering applications. Existing deep learning methods show promise but lack support for mult…
Cross-Domain Foundation Model Adaptation: Pioneering Computer Vision Models for Geophysical Data Analysis
Zhixiang Guo, Xinming Wu, Luming Liang +3
We explore adapting foundation models (FMs) from the computer vision domain to geoscience. FMs, large neural networks trained on massive datasets, excel in diverse tasks with remar…
FORA: Fast-Forward Caching in Diffusion Transformer Acceleration
Pratheba Selvaraju, Tianyu Ding, Tianyi Chen +2
Diffusion transformers (DiT) have become the de facto choice for generating high-quality images and videos, largely due to their scalability, which enables the construction of larg…
AdaContour: Adaptive Contour Descriptor with Hierarchical Representation
Tianyu Ding, Jinxin Zhou, Tianyi Chen +3
Existing angle-based contour descriptors suffer from lossy representation for non-starconvex shapes. By and large, this is the result of the shape being registered with a single gl…
S3Editor: A Sparse Semantic-Disentangled Self-Training Framework for Face Video Editing
Guangzhi Wang, Tianyi Chen, Kamran Ghasedi +6
Face attribute editing plays a pivotal role in various applications. However, existing methods encounter challenges in achieving high-quality results while preserving identity, edi…
LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery
Tianyi Chen, Tianyu Ding, Badal Yadav +2
Large Language Models (LLMs) have transformed the landscape of artificial intelligence, while their enormous size presents significant challenges in terms of computational costs. W…