AI Engineering Institute: 3Fine-tuning (fine-tuning of large language models)

With the rapid development and wide application of large-scale language modeling technology, its potential security risks have increasingly become the focus of the industry's attention. In order to address these challenges, many of the world's top technology companies, standardization organizations and research institutions have constructed and released their own security frameworks. In this paper, we will analyze nine of them...

In the field of Large Language Modeling (LLM) research, the model's Leap-of-Thought ability, i.e., creativity, is no less important than the logical reasoning ability represented by Chain-of-Thought. However, there is still a relative lack of in-depth discussions and valid assessment methods for LLM creativity, which in ...

Mastering Claude Code: Hands-on Agentic Coding Tips from the Front Lines Claude Code is a command line tool for Agentic Coding. By Agentic Coding, we mean giving AI a certain degree of autonomy to understand tasks, plan steps, and perform actions (such as...

The GPT-4.1 family of models offers significant improvements in coding, instruction adherence, and long context processing capabilities over GPT-4o. Specifically, it performs better on code generation and repair tasks, understands and executes complex instructions more accurately, and can efficiently handle longer input text. This hinted work ...

1. INTRODUCTION In today's information explosion, a large amount of knowledge is stored in the form of tables in web pages, Wikipedia and relational databases. However, traditional question and answer systems often struggle to handle complex queries across multiple tables, which has become a major challenge in the field of artificial intelligence. To address this challenge, researchers ...

As the capabilities of large-scale language models (LLMs) evolve at a rapid pace, traditional benchmark tests, such as MMLU, are gradually showing limitations in distinguishing top models. Relying on knowledge quizzes or standardized tests alone, it has become difficult to comprehensively measure the nuanced capabilities of models that are critical in real-world interactions, such as emotional intelligence, creative...

The development of large language models (LLMs) is rapidly changing, and their reasoning ability has become a key indicator of their intelligence level. In particular, models with long reasoning capabilities, such as OpenAI's o1, DeepSeek-R1, QwQ-32B, and Kimi K1.5, which simulate the human deep thinking process by solving compound...

INTRODUCTION In recent years, Large Language Models (LLMs) have made impressive progress in the field of Artificial Intelligence, and their powerful language comprehension and generation capabilities have led to a wide range of applications in several domains. However, LLMs still face many challenges when dealing with complex tasks that require the invocation of external tools. For example, ...