Papers with graph-based RAGs
FinGEAR: Financial Mapping-Guided Enhanced Answer Retrieval (2025.findings-emnlp)
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| Challenge: | FinGEAR provides a retrieval framework tailored to financial documents . standard retrieval-augmented generation models underuse financial disclosures . |
| Approach: | FinGEAR combines a finance lexicon for Item-level guidance and hierarchical indices for within-Item search. |
| Outcome: | FinGEAR improves accuracy and accuracy on 10-Ks with a FinQA dataset. |
MS-RAG: Simple and Effective Multi-Semantic Retrieval-Augmented Generation (2025.emnlp-main)
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| Challenge: | Existing methods for large language models suffer from poor indexing and inference speed . graph-based RAGs heavily rely on LLM for retrieval thus inference slow . |
| Approach: | They propose retrieval-augmented generation (RAG) which integrates knowledge with dense vectors to build a multi-semantic RAG. |
| Outcome: | The proposed method achieves state-of-the-art performance with faster inference speed compared to existing methods . |