S-Path-RAG: Semantic-Aware Shortest-Path Retrieval Augmented Generation for Multi-Hop Knowledge Graph Question Answering

1. 1Enumerate bounded-length candidate paths using a hybrid strategy
2. 2Learn a differentiable path scorer with a contrastive path loss function
3. 3Apply the framework to multi-hop question answering tasks over large knowledge graphs
4. 4Evaluate the performance of S-Path-RAG using metrics such as accuracy and F1-score

AI engineers and researchers on a team can benefit from S-Path-RAG to improve question answering over large knowledge graphs, while data scientists can apply the framework to real-world problems

💡 S-Path-RAG improves multi-hop question answering by enumerating semantically weighted candidate paths

🤖 S-Path-RAG: semantic-aware shortest-path retrieval for multi-hop question answering