Papers by Eugenio Martínez-Cámara

1 papers
The Problem of Ambiguity in Table Question Answering (2026.findings-eacl)

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Challenge: Existing approaches to question answering on tabular data have limited capabilities due to ambiguousness inherent to tabular datasets.
Approach: They propose to use large language models to answer questions on tabular data by analyzing tabular tables and detecting ambiguity.
Outcome: The proposed model can detect ambiguity in tabular data and provide an initial ground for a deeper discussion on how to approach it in the age of LLMs.

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