Instance-Adaptive Prompts as Context for Time-Series Foundation Models
Longer histories can improve time-series foundation models (TSFMs), but require substantially higher inference cost. We therefore ask whether contextual information can be provided more efficiently through a compact set of learned token embeddings. We introduce PaCTS, which generates a small set of instance-adaptive la...
Ze-Hao Xiao, Shi-Feng Xie, Lei Zan et al.
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