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The improvement in translating natural language to structured query language (SQL) can be attributed to the advancements in large language models (LLMs).
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding
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Multi-Task Learning with Deep Neural Networks: A Survey
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Neo4j - The World’s Leading Graph Database
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Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer. In International Conference on Learning Representations
Noam Shazeer, *Azalia Mirhoseini, *Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean. 2017 · 2017
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Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . 3911–3921
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Which Tasks Should Be Learned Together in Multi-task Learning?. In Proceedings of the 37th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 119) , Hal Daumé III and Aarti Singh (Eds.). PMLR, 9120–9132
Trevor Standley, Amir Zamir, Dawn Chen, Leonidas Guibas, Jitendra Malik, and Silvio Savarese. 2020 · 2020
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Chase: A Large-Scale and Pragmatic Chinese Dataset for Cross-Database Context-Dependent Text-to-SQL. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, Online, 2316–2331
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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A Survey on Multi-Task Learning
Yu Zhang and Qiang Yang. 2022 · 2021
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GLaM: Efficient Scaling of Language Models with Mixture-of-Experts. In Proceedings of the 39th International Conference on Machine Learning (Proceedings of Machine Learning Research, Vol. 162) , Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvari, Gang Niu, and Sivan Sabato (Eds.). PMLR, 5547–5569
Nan Du, Yanping Huang, Andrew M Dai, Simon Tong, Dmitry Lepikhin, Yuanzhong Xu, Maxim Krikun, Yanqi Zhou, Adams Wei Yu, Orhan Firat, Barret Zoph, Liam Fedus, Maarten P Bosma, Zongwei Zhou, Tao Wang, Emma Wang, Kellie Webster, Marie Pellat, Kevin Robinson, Kathleen Meier-Hellstern, Toju Duke, Lucas Dixon, Kun Zhang, Quoc Le, Yonghui Wu, Zhifeng Chen, and Claire Cui. 2022 · 2022
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Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
William Fedus, Barret Zoph, and Noam Shazeer. 2022 · 2022
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Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints. In The Eleventh International Conference on Learning Representations
Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, Carlos Riquelme Ruiz, Basil Mustafa, Joshua Ainslie, Yi Tay, Mostafa Dehghani, and Neil Houlsby. 2022 · 2022
Cited alongside, same era.
Nebula Graph: An open source distributed graph database
Min Wu, Xinglu Yi, Hui Yu, Yu Liu, and Yujue Wang. 2022 · 2022
Cited alongside, same era.
Designing Effective Sparse Expert Models. In 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) . 1044–1044
Barret Zoph. 2022 · 2022
Cited alongside, same era.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models
Wenfeng Feng, Chuzhan Hao, Yuewei Zhang, Yu Han, and Hao Wang. 2024 · 2024
Closest in time.
Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
Dawei Gao, Haibin Wang, Yaliang Li, Xiuyu Sun, Yichen Qian, Bolin Ding, and Jingren Zhou. 2024 · 2024
Closest in time.
Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2024 · 2024
Closest in time.
CodeS: Towards Building Open-source Language Models for Text-to-SQL
Haoyang Li, Jing Zhang, Hanbing Liu, Ju Fan, Xiaokang Zhang, Jun Zhu, Renjie Wei, Hongyan Pan, Cuiping Li, and Hong Chen. 2024d · 2024
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Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
Cited alongside, same era.
Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al · 2023
Cited alongside, same era.
MultiSpider: towards benchmarking multilingual text-to-SQL semantic parsing. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 37. 12745–12753
Longxu Dou, Yan Gao, Mingyang Pan, Dingzirui Wang, Wanxiang Che, Dechen Zhan, and Jian-Guang Lou. 2023 · 2023
Cited alongside, same era.
Catsql: Towards real world natural language to sql applications
Han Fu, Chang Liu, Bin Wu, Feifei Li, Jian Tan, and Jianling Sun. 2023 · 2023
Cited alongside, same era.
DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction. In Thirty-seventh Conference on Neural Information Processing Systems
Mohammadreza Pourreza and Davood Rafiei. 2023 · 2023
Cited alongside, same era.
LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
Cited alongside, same era.
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models
Damai Dai, Chengqi Deng, Chenggang Zhao, R. X. Xu, Huazuo Gao, Deli Chen, Jiashi Li, Wangding Zeng, Xingkai Yu, Y. Wu, Zhenda Xie, Y. K. Li, Panpan Huang, Fuli Luo, Chong Ruan, Zhifang Sui, and Wenfeng Liang. 2024 · 2024
Cited alongside, same era.
MixLoRA: Enhancing Large Language Models Fine-Tuning with LoRA-based Mixture of Experts
Dengchun Li, Yingzi Ma, Naizheng Wang, Zhengmao Ye, Zhiyuan Cheng, Yinghao Tang, Yan Zhang, Lei Duan, Jie Zuo, Cal Yang, and Mingjie Tang. 2024b
Cited in the paper.
Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls
Jinyang Li, Binyuan Hui, Ge Qu, Jiaxi Yang, Binhua Li, Bowen Li, Bailin Wang, Bowen Qin, Ruiying Geng, Nan Huo, et al · 2024
Closest in time.
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
Bin Lin, Zhenyu Tang, Yang Ye, Jiaxi Cui, Bin Zhu, Peng Jin, Junwu Zhang, Munan Ning, and Li Yuan. 2024 · 2024
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Code Llama: Open Foundation Models for Code
Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, Sten Sootla, Itai Gat, Xiaoqing Ellen Tan, Yossi Adi, Jingyu Liu, Romain Sauvestre, Tal Remez, Jérémy Rapin, Artyom Kozhevnikov, Ivan Evtimov, Joanna Bitton, Manish Bhatt, Cristian Canton Ferrer, Aaron Grattafiori, Wenhan Xiong, Alexandre Défossez, Jade Copet, Faisal Azhar, Hugo Touvron, Louis Martin, Nicolas Usunier, Thomas Scialom, and Gabriel Synnaeve. 2024 · 2024
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Xun Wu, Shaohan Huang, and Furu Wei. 2024 · 2024
Closest in time.
OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models
Fuzhao Xue, Zian Zheng, Yao Fu, Jinjie Ni, Zangwei Zheng, Wangchunshu Zhou, and Yang You. 2024 · 2024
Closest in time.
Sparse MoE with Language Guided Routing for Multilingual Machine Translation. In The Twelfth International Conference on Learning Representations
Xinyu Zhao, Xuxi Chen, Yu Cheng, and Tianlong Chen. 2024 · 2024
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R 3 R^{3} -NL2GQL: A Model Coordination and Knowledge Graph Alignment Approach for NL2GQL
Yuhang Zhou, Yu He, Siyu Tian, Yuchen Ni, Zhangyue Yin, Xiang Liu, Chuanjun Ji, Sen Liu, Xipeng Qiu, Guangnan Ye, and Hongfeng Chai. 2024 · 2024
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