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Lotus: Learning to Understand Time-series by Learning to Forecast
Not provided in the abstract
time-serieslanguage modelsforecastingrepresentation learning
2610.18877
Builder Relevance
2h ago80%
Abstract
LOTUS introduces forecast grounding as a pretraining principle for time-series language models, enhancing their ability to retain temporal information.
Reality Card
Core Claim
LOTUS achieves the best average performance on downstream tasks with minimal trainable parameters, outperforming the strongest matched baseline by 3.36%.
Method / Result
59.91% accuracy across six downstream evaluation datasets.
Limitations
The paper does not specify potential limitations or reproducibility concerns.
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