Summary of The Performance Of the Lstm-based Code Generated by Large Language Models (llms) in Forecasting Time Series Data, By Saroj Gopali et al.
The Performance of the LSTM-based Code Generated by Large Language Models (LLMs) in Forecasting Time Series Data
by Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin
First submitted to arxiv on: 27 Nov 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper investigates the performance of large language models (LLMs) such as ChatGPT, PaLM, LLama, and Falcon in generating deep learning models for analyzing time series data. The study compares the LLMs’ ability to generate executable codes for specific datasets and evaluates their performance using LSTM models as a benchmark. Results show that some LLMs can produce comparable models with manually crafted and optimized LSTM models, while others like ChatGPT outperform in generating more accurate models. Temperature parameter configurations also affect the goodness of generated models. The findings can benefit data analysts and practitioners who want to leverage generative AIs for producing good prediction models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Deep learning models are super smart machines that can analyze big amounts of data, but they’re hard to make by hand. This paper looks at how four special computers (ChatGPT, PaLM, LLama, and Falcon) do with making these models. They tested these computers on analyzing important types of data called time series data. The results are mixed, but some computers did really well! One computer, ChatGPT, was especially good at making accurate models. The study also found that a special setting on the computers, called “temperature”, makes them do better or worse. This research can help people who need to make predictions from big datasets use these super smart machines. |
Keywords
» Artificial intelligence » Deep learning » Llama » Lstm » Palm » Temperature » Time series
