activity
20182023
most citedEnhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting

1.1k citations · 1.5k across the 15 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CL2023★ 5 cited

Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection

Jun Yan, Vikas Yadav, Shiyang Li +6

Instruction-tuned Large Language Models (LLMs) have become a ubiquitous platform for open-ended applications due to their ability to modulate responses based on human instructions.…

cs.CL2023★ 15 cited

AlpaGasus: Training A Better Alpaca with Fewer Data

Lichang Chen, Shiyang Li, Jun Yan +8

Large language models (LLMs) strengthen instruction-following capability through instruction-finetuning (IFT) on supervised instruction/response data. However, widely used IFT data…

cs.CL2023

Graph Reasoning for Question Answering with Triplet Retrieval

Shiyang Li, Yifan Gao, Haoming Jiang +5

Answering complex questions often requires reasoning over knowledge graphs (KGs). State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which ar…

cs.CL2023★ 3 cited

Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting

Xinlu Zhang, Shiyang Li, Xianjun Yang +3

Large language models (LLMs) demonstrate remarkable medical expertise, but data privacy concerns impede their direct use in healthcare environments. Although offering improved data…

cs.LG2023★ 14 cited

Time Series as Images: Vision Transformer for Irregularly Sampled Time Series

Zekun Li, Shiyang Li, Xifeng Yan

Irregularly sampled time series are increasingly prevalent, particularly in medical domains. While various specialized methods have been developed to handle these irregularities, e…