Papers by Jeonghyeon Park
TH-RAG : Topic-Based Hierarchical Knowledge Graphs for Robust Multi-hop Reasoning in Graph-based RAG Systems (2026.acl-long)
Copied to clipboard
| Challenge: | Retrieval-augmented generation (RAG) enables large language models to incorporate external knowledge at inference. |
| Approach: | They propose a hierarchical framework that organizes triplets into subtopics and topics to enhance connectivity and integrate dispersed information. |
| Outcome: | Experiments on abstractive and specific QA benchmarks show that TH-RAG outperforms strong baselines in accuracy and robustness while remaining efficient. |
ReGraphRAG: Reorganizing Fragmented Knowledge Graphs for Multi-Perspective Retrieval-Augmented Generation (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Graph-based RAG systems have been promising for enabling multi-hop reasoning . but when knowledge graphs are constructed from unstructured documents, they suffer from fragmentation . |
| Approach: | They propose a framework to reconstruct and enrich fragmented knowledge graphs . they propose three core components: Graph Reorganization, Perspective Expansion, and Query-aware Reranking. |
| Outcome: | The proposed framework outperforms state-of-the-art benchmarks on four benchmarks . it achieves over 80% diversity win rate and enables multi-hop reasoning . |