Papers with HybridQA dataset

2 papers
SUQL: Conversational Search over Structured and Unstructured Data with Large Language Models (2024.findings-naacl)

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Challenge: SUQL is a conversational language that supports the generality of hybrid data access for large knowledge corpora.
Approach: They propose a conversational agent that supports the full generality of hybrid data access for large knowledge corpora using SUQL.
Outcome: The proposed language can handle hybrid data sources.
MuGER2: Multi-Granularity Evidence Retrieval and Reasoning for Hybrid Question Answering (2022.findings-emnlp)

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Challenge: Conventional HQA models retrieve coarse- or fine-grained evidence to reason the answer . however, they neglect a more general scenario requiring reasoning over heterogeneous data to answer a question.
Approach: They propose a multi-granularity evidence retrieval and reasoning approach to answer questions over heterogeneous data using tables and passages linked to table cells.
Outcome: The proposed approach significantly boosts the performance on the HybridQA dataset.

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