Speaking Numbers to LLMs: Multi-Wavelet Number Embeddings for Time Series Forecasting

arXiv:2606. 26487v1 Announce Type: new Abstract: Large language models (LLMs) are attractive for context-aware time series forecasting because they can integrate heterogeneous textual signals, yet their discrete, language-oriented tokenization and embedding interfaces are misaligned with continuous numerical values, often harming numerical ordering and forecasting reliability.