Deep learning: Systematic review, models, challenges, and research directions

T Talaei Khoei, H Ould Slimane… - Neural Computing and …, 2023 - Springer
The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …

A Survey of NL2SQL with Large Language Models: Where are we, and where are we going?

X Liu, S Shen, B Li, P Ma, R Jiang, Y Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
Translating users' natural language queries (NL) into SQL queries (ie, NL2SQL) can
significantly reduce barriers to accessing relational databases and support various …

Text-to-sql empowered by large language models: A benchmark evaluation

D Gao, H Wang, Y Li, X Sun, Y Qian, B Ding… - arxiv preprint arxiv …, 2023 - arxiv.org
Large language models (LLMs) have emerged as a new paradigm for Text-to-SQL task.
However, the absence of a systematical benchmark inhibits the development of designing …

Chain-of-table: Evolving tables in the reasoning chain for table understanding

Z Wang, H Zhang, CL Li, JM Eisenschlos… - arxiv preprint arxiv …, 2024 - arxiv.org
Table-based reasoning with large language models (LLMs) is a promising direction to tackle
many table understanding tasks, such as table-based question answering and fact …

[PDF][PDF] Unifying the perspectives of nlp and software engineering: A survey on language models for code

Z Zhang, C Chen, B Liu, C Liao, Z Gong… - arxiv preprint arxiv …, 2023 - simg.baai.ac.cn
In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …

Xpert: Empowering incident management with query recommendations via large language models

Y Jiang, C Zhang, S He, Z Yang, M Ma, S Qin… - Proceedings of the …, 2024 - dl.acm.org
Large-scale cloud systems play a pivotal role in modern IT infrastructure. However, incidents
occurring within these systems can lead to service disruptions and adversely affect user …

Chase-sql: Multi-path reasoning and preference optimized candidate selection in text-to-sql

M Pourreza, H Li, R Sun, Y Chung, S Talaei… - arxiv preprint arxiv …, 2024 - arxiv.org
In tackling the challenges of large language model (LLM) performance for Text-to-SQL tasks,
we introduce CHASE-SQL, a new framework that employs innovative strategies, using test …

Benchmarking the text-to-sql capability of large language models: A comprehensive evaluation

B Zhang, Y Ye, G Du, X Hu, Z Li, S Yang, CH Liu… - arxiv preprint arxiv …, 2024 - arxiv.org
Large Language Models (LLMs) have emerged as a powerful tool in advancing the Text-to-
SQL task, significantly outperforming traditional methods. Nevertheless, as a nascent …

A survey of neural code intelligence: Paradigms, advances and beyond

Q Sun, Z Chen, F Xu, K Cheng, C Ma, Z Yin… - arxiv preprint arxiv …, 2024 - arxiv.org
Neural Code Intelligence--leveraging deep learning to understand, generate, and optimize
code--holds immense potential for transformative impacts on the whole society. Bridging the …

SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergy

T Zhang, C Chen, C Liao, J Wang, X Zhao, H Yu… - arxiv preprint arxiv …, 2024 - arxiv.org
Text-to-SQL conversion is a critical innovation, simplifying the transition from complex SQL
to intuitive natural language queries, especially significant given SQL's prevalence in the job …