A survey on employing large language models for text-to-sql tasks
L Shi, Z Tang, N Zhang, X Zhang, Z Yang - arXiv preprint arXiv …, 2024 - arxiv.org
The increasing volume of data in relational databases and the expertise needed for writing
SQL queries pose challenges for users to access and analyze data. Text-to-SQL (Text2SQL) …
SQL queries pose challenges for users to access and analyze data. Text-to-SQL (Text2SQL) …
Large language model for table processing: A survey
Tables, typically two-dimensional and structured to store large amounts of data, are
essential in daily activities like database queries, spreadsheet calculations, and generating …
essential in daily activities like database queries, spreadsheet calculations, and generating …
Large language models for tabular data: Progresses and future directions
Tables contain a significant portion of the world's structured information. The ability to
efficiently and accurately understand, process, reason about, analyze, and generate tabular …
efficiently and accurately understand, process, reason about, analyze, and generate tabular …
Large language models meet nlp: A survey
While large language models (LLMs) like ChatGPT have shown impressive capabilities in
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …
A survey of aiops for failure management in the era of large language models
As software systems grow increasingly intricate, Artificial Intelligence for IT Operations
(AIOps) methods have been widely used in software system failure management to ensure …
(AIOps) methods have been widely used in software system failure management to ensure …
Codexgraph: Bridging large language models and code repositories via code graph databases
Large Language Models (LLMs) excel in stand-alone code tasks like HumanEval and
MBPP, but struggle with handling entire code repositories. This challenge has prompted …
MBPP, but struggle with handling entire code repositories. This challenge has prompted …
Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning
Reinforcement learning from human feedback (RLHF) and AI-generated feedback (RLAIF)
have become prominent techniques that significantly enhance the functionality of pre-trained …
have become prominent techniques that significantly enhance the functionality of pre-trained …
Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL
Generating accurate SQL according to natural language questions (text-to-SQL) is a long-
standing problem since it is challenging in user question understanding, database schema …
standing problem since it is challenging in user question understanding, database schema …
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
We introduce TableLLM, a robust large language model (LLM) with 13 billion parameters,
purpose-built for proficiently handling tabular data manipulation tasks, whether they are …
purpose-built for proficiently handling tabular data manipulation tasks, whether they are …
Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models
The rapid advancement in text-to-video (T2V) generative models has enabled the synthesis
of high-fidelity video content guided by textual descriptions. Despite this significant progress …
of high-fidelity video content guided by textual descriptions. Despite this significant progress …