JohnJiang12138/CMRP
Cross-modal Reinforced Prompting for Graph and Language Tasks, KDD 2024.
This project helps machine learning engineers and researchers improve how large language models (LLMs) understand and process information from both text and graph data. It takes your existing graph datasets (like knowledge graphs) and text prompts, then uses a reinforcement learning approach to generate better prompts, leading to more accurate LLM outputs for tasks involving both data types.
No commits in the last 6 months.
Use this if you are a machine learning engineer working with LLMs and need to enhance their performance on tasks that combine structured graph data with natural language.
Not ideal if you are looking for a plug-and-play solution for general text processing without graph data, or if you are not comfortable with advanced machine learning model training.
Stars
11
Forks
1
Language
Python
License
MIT
Category
Last pushed
Sep 29, 2024
Commits (30d)
0
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