Language in the Flow of Time: Time-Series-Paired Texts Weaved into a Unified Temporal Narrative

ArXi:2502.08942v3 Announce Type: replace While many advances in time series models focus exclusively on numerical data, research on multimodal time series, particularly those involving contextual textual information, remains in its infancy. With recent progress in large language models and time series learning, we revisit the integration of paired texts with time series through the Platonic Representation Hypothesis, which posits that representations of different modalities converge to shared spaces.