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cs.AI2026

TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models

Martin Maritsch, Timo Stoffregen, Thomas Kaar +36

Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, task-specific data formats, annot…

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.AI2026

Time Series Reasoning via Process-Verifiable Thinking Data Synthesis and Scheduling for Tailored LLM Reasoning

Jiahui Zhou, Dan Li, Boxin Li +6

Time series is a pervasive data type across various application domains, rendering the reasonable solving of diverse time series tasks a long-standing goal. Recent advances in larg…

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…