27 citations · 68 across the 24 of their papers we have counts for
4 papers · 1 filter
Open-Source Multimodal Moxin Models with Moxin-VLM and Moxin-VLA
Pu Zhao, Arash Akbari, Xuan Shen +16
Recently, Large Language Models (LLMs) have undergone a significant transformation, marked by a rapid rise in both their popularity and capabilities. Leading this evolution are pro…
TSLA: A Task-Specific Learning Adaptation for Semantic Segmentation on Autonomous Vehicles Platform
Jun Liu, Zhenglun Kong, Pu Zhao +9
Autonomous driving platforms encounter diverse driving scenarios, each with varying hardware resources and precision requirements. Given the computational limitations of embedded d…
Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation
Zhenglun Kong, Zheng Zhan, Shiyue Hou +10
Large language models (LLMs) have shown remarkable promise but remain challenging to continually improve through traditional finetuning, particularly when integrating capabilities…
RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation
Jun Liu, Zhenglun Kong, Peiyan Dong +10
Fine-tuning helps large language models (LLM) recover degraded information and enhance task performance. Although Low-Rank Adaptation (LoRA) is widely used and effective for fine-t…