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20232026
most citedContext-Alignment: Activating and Enhancing LLM Capabilities in Time Series

1 citations · 3 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

GENSR: Symbolic Regression Based in Equation Generative Space

Qian Li, Yuxiao Hu, Juncheng Liu +1

Symbolic Regression (SR) tries to reveal the hidden equations behind observed data. However, most methods search within a discrete equation space, where the structural modification…

cs.LG2025★ 1 cited

Context-Alignment: Activating and Enhancing LLM Capabilities in Time Series

Yuxiao Hu, Qian Li, Dongxiao Zhang +2

Recently, leveraging pre-trained Large Language Models (LLMs) for time series (TS) tasks has gained increasing attention, which involves activating and enhancing LLMs' capabilities…

cs.LG2023

Multi-spatial Multi-temporal Air Quality Forecasting with Integrated Monitoring and Reanalysis Data

Yuxiao Hu, Qian Li, Xiaodan Shi +2

Accurate air quality forecasting is crucial for public health, environmental monitoring and protection, and urban planning. However, existing methods fail to effectively utilize mu…

cs.LG2023★ 1 cited

Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training

Qian Li, Yuxiao Hu, Yinpeng Dong +2

Adversarial training is often formulated as a min-max problem, however, concentrating only on the worst adversarial examples causes alternating repetitive confusion of the model, i…

cs.LG2023

CLeaRForecast: Contrastive Learning of High-Purity Representations for Time Series Forecasting

Jiaxin Gao, Yuxiao Hu, Qinglong Cao +2

Time series forecasting (TSF) holds significant importance in modern society, spanning numerous domains. Previous representation learning-based TSF algorithms typically embrace a c…