144 citations · 151 across the 4 of their papers we have counts for
4 papers
How to Unlock Time Series Editing? Diffusion-Driven Approach with Multi-Grained Control
Hao Yu, Chu Xin Cheng, Runlong Yu +4
Recent advances in time series generation have shown promise, yet controlling properties in generated sequences remains challenging. Time Series Editing (TSE) - making precise modi…
Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey
Aoran Gan, Hao Yu, Kai Zhang +5
Recent advancements in Retrieval-Augmented Generation (RAG) have revolutionized natural language processing by integrating Large Language Models (LLMs) with external information re…
CAFe: Unifying Representation and Generation with Contrastive-Autoregressive Finetuning
Hao Yu, Zhuokai Zhao, Shen Yan +7
The rapid advancement of large vision-language models (LVLMs) has driven significant progress in multimodal tasks, enabling models to interpret, reason, and generate outputs across…
Evaluation of Retrieval-Augmented Generation: A Survey
Hao Yu, Aoran Gan, Kai Zhang +3
Retrieval-Augmented Generation (RAG) has recently gained traction in natural language processing. Numerous studies and real-world applications are leveraging its ability to enhance…