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cs.AI2026
TSQAgent: Rating Time Series Data Quality via Dedicated Agentic Reasoning
Shunyu Wu, Dan Li, Haozheng Ye +6
Assessing the quality of time series (TS) data is fundamental yet inherently challenging due to the multifaceted nature of quality dimensions. Recently, large language models (LLMs…
cs.AI2025
Integrating Time Series into LLMs via Multi-layer Steerable Embedding Fusion for Enhanced Forecasting
Zhuomin Chen, Dan Li, Jiahui Zhou +4
Time series (TS) data are ubiquitous across various application areas, rendering time series forecasting (TSF) a fundamental task. With the astounding advances in large language mo…
cs.AI2025
Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision
Jiahui Zhou, Dan Li, Lin Li +5
The reasoning capabilities of large language models (LLMs) have significantly advanced their performance by enabling in-depth understanding of diverse tasks. With growing interest…