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Large language models (LLMs), with demonstrated reasoning abilities across multiple domains, are largely underexplored for time-series reasoning (TsR), which is ubiquitous in the real world.
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Reasoning with probabilistic and deterministic graphical models: Exact algorithms
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Large language models are zero-shot reasoners
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evaluation of flusight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
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Promptcast: A new prompt-based learning paradigm for time series forecasting
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Are transformers effective for time series forecasting?
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To cot or not to cot? chain-of-thought helps mainly on math and symbolic reasoning
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On the out-of-distribution generalization of multimodal large language models
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