Papers by Soohyeong Kim
Bidirectional Masked Self-attention and N-gram Span Attention for Constituency Parsing (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing attention mechanisms for constituency parsing lack directional information needed to form sentence spans. |
| Approach: | They propose a bidirectional masked and N-gram span Attention model which captures the explicit dependencies between each word and enhances the representation of the output span vectors. |
| Outcome: | The proposed model achieves state-of-the-art performance on the Penn Treebank and Chinese Penn TreeBank datasets with F1 scores of 96.47 and 94.15 respectively. |
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 . |