Papers by Xingyou Yin

1 papers
Enhancing Zero-Shot Time Series Forecasting in Off-the-Shelf LLMs via Noise Injection Prompting (2026.findings-acl)

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Challenge: Existing work relies on fine-tuning specialized modules to bridge this gap, but a novel approach is proposed to leverage off-the-shelf LLMs without any fine- tuning whatsoever.
Approach: They propose a method to inject noise into the raw time series before tokenization to induce the model to extrapolate based on robust underlying temporal patterns rather than superficial numerical artifacts.
Outcome: The proposed approach overcomes the brittleness of fully frozen models by injecting noise into the raw TS before tokenization.

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