Summary of Momq: Mixture-of-experts Enhances Multi-dialect Query Generation Across Relational and Non-relational Databases, by Zhisheng Lin et al.
MoMQ: Mixture-of-Experts Enhances Multi-Dialect Query Generation across Relational and Non-Relational Databases
by Zhisheng Lin, Yifu Liu, Zhiling Luo, Jinyang Gao, Yu Li
First submitted to arxiv on: 24 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Databases (cs.DB); Machine Learning (cs.LG)
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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 proposed framework, MoMQ, is a novel Mixture-of-Experts-based multi-dialect query generation approach designed to tackle the challenges of generating SQL queries across multiple database dialects. The framework employs a dialect expert group for each dialect and a multi-level routing strategy to handle dialect-specific knowledge, reducing interference during query generation. Additionally, a shared expert group is introduced to address data imbalance, facilitating the transfer of common knowledge from high-resource dialects to low-resource ones. The MoMQ framework was evaluated on a high-quality multi-dialect query generation benchmark that covers relational and non-relational databases such as MySQL, PostgreSQL, Cypher for Neo4j, and nGQL for NebulaGraph. Experimental results show that MoMQ performs effectively and robustly even in resource-imbalanced scenarios. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MoMQ is a new way to help computers understand different languages of data storage. Right now, computers are great at understanding one type of language, but they struggle when it comes to understanding many different types of data storage languages. This is because each type of data storage has its own special rules and ways of communicating. MoMQ helps solve this problem by using a combination of experts who know the specific rules of each data storage language. This allows MoMQ to generate SQL queries that can be understood by many different types of databases. |
Keywords
* Artificial intelligence * Mixture of experts
