19 citations · 35 across the 11 of their papers we have counts for
5 papers · 1 filter
VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
Mouxiang Chen, Lefei Shen, Zhuo Li +3
Foundation models have emerged as a promising approach in time series forecasting (TSF). Existing approaches either repurpose large language models (LLMs) or build large-scale time…
Towards Explainable Vulnerability Detection with Large Language Models
Qiheng Mao, Zhenhao Li, Xing Hu +3
Software vulnerabilities pose significant risks to the security and integrity of software systems. Although prior studies have explored vulnerability detection using deep learning…
Advancing Graph Representation Learning with Large Language Models: A Comprehensive Survey of Techniques
Qiheng Mao, Zemin Liu, Chenghao Liu +2
The integration of Large Language Models (LLMs) with Graph Representation Learning (GRL) marks a significant evolution in analyzing complex data structures. This collaboration harn…
PEMT: Multi-Task Correlation Guided Mixture-of-Experts Enables Parameter-Efficient Transfer Learning
Zhisheng Lin, Han Fu, Chenghao Liu +2
Parameter-efficient fine-tuning (PEFT) has emerged as an effective method for adapting pre-trained language models to various tasks efficiently. Recently, there has been a growing…
JumpCoder: Go Beyond Autoregressive Coder via Online Modification
Mouxiang Chen, Hao Tian, Zhongxin Liu +2
While existing code large language models (code LLMs) exhibit impressive capabilities in code generation, their autoregressive sequential generation inherently lacks reversibility.…