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Proposes TempoWave, a plug-and-play temporal wavelet digit interface that maps time series observations into digit-wise embeddings from multi-wavelet coefficients, improving LLM-based time series forecasting and achieving state-of-the-art on multiple benchmarks.
This paper presents a methodology for delineating concepts and training linear probes to detect them in LLM embeddings, using four example concepts across three models. The work aims to enable scalable monitoring of LLM internal representations.