3 citations · 6 across the 18 of their papers we have counts for
5 papers · 1 filter
TableTime: Reformulating Time Series Classification as Training-Free Table Understanding with Large Language Models
Jiahao Wang, Mingyue Cheng, Qingyang Mao +5
Large language models (LLMs) have demonstrated their effectiveness in multivariate time series classification (MTSC). Effective adaptation of LLMs for MTSC necessitates informative…
Conditional Denoising Meets Polynomial Modeling: A Flexible Decoupled Framework for Time Series Forecasting
Jintao Zhang, Mingyue Cheng, Xiaoyu Tao +2
Time series forecasting models are becoming increasingly prevalent due to their critical role in decision-making across various domains. However, most existing approaches represent…
TimeDART: A Diffusion Autoregressive Transformer for Self-Supervised Time Series Representation
Daoyu Wang, Mingyue Cheng, Zhiding Liu +1
Self-supervised learning has garnered increasing attention in time series analysis for benefiting various downstream tasks and reducing reliance on labeled data. Despite its effect…
Revisiting the Solution of Meta KDD Cup 2024: CRAG
Jie Ouyang, Yucong Luo, Mingyue Cheng +4
This paper presents the solution of our team APEX in the Meta KDD CUP 2024: CRAG Comprehensive RAG Benchmark Challenge. The CRAG benchmark addresses the limitations of existing QA…
Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study
Shuo Yu, Mingyue Cheng, Qi Liu +6
Retrieval-augmented generation (RAG) is increasingly recognized as an effective approach to mitigating the hallucination of large language models (LLMs) through the integration of…