Search Results for author:
Found 7 papers, 5 papers with code
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
We also propose a new high-throughput framework to alleviate the computation and memory bottlenecks during the training and inference of MOE models.
BadPart: Unified Black-box Adversarial Patch Attacks against Pixel-wise Regression Tasks
Our attack prototype, named BadPart, is evaluated on both MDE and OFE tasks, utilizing a total of 7 models.
Couler: Unified Machine Learning Workflow Optimization in Cloud
This variety poses a challenge for end-users in terms of mastering different engine APIs.
ASPEN: High-Throughput LoRA Fine-Tuning of Large Language Models with a Single GPU
Transformer-based large language models (LLMs) have demonstrated outstanding performance across diverse domains, particularly when fine-turned for specific domains.
DLRover: An Elastic Deep Training Extension with Auto Job Resource Recommendation
The resource configuration of a job deeply affect this job's performance (e. g., training throughput, resource utilization, and completion rate).
SQLFlow: A Bridge between SQL and Machine Learning
Previous database systems extended their SQL dialect to support ML.
A Natural-language-based Visual Query Approach of Uncertain Human Trajectories
Visual querying is essential for interactively exploring massive trajectory data.
