Papers by Soham Palande
Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmark (2024.emnlp-main)
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Elizabeth Fons, Rachneet Kaur, Soham Palande, Zhen Zeng, Tucker Balch, Manuela Veloso, Svitlana Vyetrenko
| Challenge: | Large Language Models (LLMs) are a critical tool for time series analysis and reporting in many fields, including healthcare, finance, climate, and many more. |
| Approach: | They propose a framework for rigorously evaluating the capabilities of Large Language Models (LLMs) on time series understanding, encompassing both univariate and multivariate forms. |
| Outcome: | The proposed framework delineates various characteristics inherent in time series data. |