Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …

The integration of Large Language Models (LLMs) and Edge Intelligence (EI) introduces a
groundbreaking paradigm for intelligent edge devices. With their capacity for human-like …

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 …

General large language models (LLMs), represented by ChatGPT, have demonstrated
significant potential in tasks such as code generation in software engineering. This has led …

With the rise of large language models (LLMs), researchers are increasingly exploring their
applications in var ious vertical domains, such as software engineering. LLMs have …

This paper proposes a ChatGPT-based zero-shot Text-to-SQL method, dubbed C3, which
achieves 82.3\% in terms of execution accuracy on the holdout test set of Spider and …

Translating users' natural language queries (NL) into SQL queries (ie, NL2SQL) can
significantly reduce barriers to accessing relational databases and support various …

The field of AI agents is advancing at an unprecedented rate due to the capabilities of large
language models (LLMs). However, LLM-driven visual agents mainly focus on solving tasks …

The capability gap between open-source and closed-source large language models (LLMs)
remains a challenge in text-to-SQL tasks. In this paper, we introduce a synthetic data …

Analyzing network topologies and communication graphs is essential in modern network
management. However, the lack of a cohesive approach results in a steep learning curve …