Why Large Language Models Fail at Tabular Prediction
Large language models (LLMs) struggle with predictive analytics over tabular data, which is a common machine learning workload. This limitation has led to the emergence of tabular foundation models aimed at addressing this gap.
arxiv.org
2 min
8/4/2026
TabFM: A zero-shot foundation model for tabular data
TabFM is a new foundation model designed for tabular data, simplifying classification and regression workflows. It utilizes a "zero-shot" logic approach, similar to that of TimesFM, to enhance the handling of enterprise data infrastructure.
research.google
4 min
6/30/2026
Why Large Language Models Fail at Tabular Prediction
Large language models (LLMs) struggle with predictive analytics over tabular data, which is a common machine learning workload. This limitation has led to the emergence of tabular foundation models aimed at addressing this gap.
arxiv.org
2 min
8/4/2026
TabFM: A zero-shot foundation model for tabular data
TabFM is a new foundation model designed for tabular data, simplifying classification and regression workflows. It utilizes a "zero-shot" logic approach, similar to that of TimesFM, to enhance the handling of enterprise data infrastructure.
research.google
4 min
6/30/2026
Why Large Language Models Fail at Tabular Prediction
Large language models (LLMs) struggle with predictive analytics over tabular data, which is a common machine learning workload. This limitation has led to the emergence of tabular foundation models aimed at addressing this gap.
arxiv.org
2 min
8/4/2026
TabFM: A zero-shot foundation model for tabular data
TabFM is a new foundation model designed for tabular data, simplifying classification and regression workflows. It utilizes a "zero-shot" logic approach, similar to that of TimesFM, to enhance the handling of enterprise data infrastructure.
research.google
4 min
6/30/2026
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