Search Results for author:
Found 4 papers, 1 papers with code
AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models
AutoGluon-Multimodal (AutoMM) is introduced as an open-source AutoML library designed specifically for multimodal learning.
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
The Segment Anything Model (SAM) stands as a foundational framework for image segmentation.
A Transformer-Based Substitute Recommendation Model Incorporating Weakly Supervised Customer Behavior Data
The substitute-based recommendation is widely used in E-commerce to provide better alternatives to customers.
DAWN: Dual Augmented Memory Network for Unsupervised Video Object Tracking
Our Dual Augmented Memory Network (DAWN) is unique in remembering both target and background, and using an improved attention LSTM memory to guide the focus on memorized features.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
