InA-Probe improves LLM time series forecasting via instruction-aware active probing, outperforming baselines with up to 37% error reduction on seven benchmarks in one-for-all and zero-shot settings.
Adapting LLMs to time series forecasting via temporal het- erogeneity modeling and semantic alignment
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InA-Probe: Instruction-Aware Active Probing for Time Series Forecasting with LLMs
InA-Probe improves LLM time series forecasting via instruction-aware active probing, outperforming baselines with up to 37% error reduction on seven benchmarks in one-for-all and zero-shot settings.