BlendSQL: A Scalable Dialect for Unifying Hybrid Question Answering in Relational Algebra (2024.findings-acl)
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| Challenge: | Existing hybrid question answering systems use a "prompt-and-pray" paradigm . context size limitations limit ability of many transformer-based LLMs to fit into a given prompt . |
| Approach: | They propose a superset of SQLite to act as a unified dialect for orchestrating reasoning across unstructured and structured data. |
| Outcome: | The proposed framework scales to massive datasets and improves performance while using 35% fewer tokens. |
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| Challenge: | Existing approaches to answer multi-hop questions are query-agnostic and the extracted facts are ambiguous as they lack context. |
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| Challenge: | Recent studies have demonstrated that Large Language Models (LLMs) have impressive capabilities in a variety of domains and tasks. |
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Barlas Oguz, Xilun Chen, Vladimir Karpukhin, Stan Peshterliev, Dmytro Okhonko, Michael Schlichtkrull, Sonal Gupta, Yashar Mehdad, Scott Yih
| Challenge: | a recent study aims to answer factual questions using a structured knowledge base (KBQA). |
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