Papers with suboptimal retrieval
Retrieval-Augmented Parsing for Complex Graphs by Exploiting Structure and Uncertainty (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Retrieval augmentation is effective for large graph parsing tasks, but can fail to identify the most informative exemplars . structure-aware and uncertainty-guided adaptive retrieval (SUGAR) exploits two unique sources of information: structural similarity and model uncertainty. |
| Approach: | They propose a structure-aware and uncertainty-guided adaptive retrieval approach that exploits structural similarity and model uncertainty to improve retrieval-augmented parsing for complex graph problems. |
| Outcome: | The proposed method improves retrieval-augmented parsing for graph parsers with large output graphs and non-trivial structure. |
Can we Retrieve Everything All at Once? ARM: An Alignment-Oriented LLM-based Retrieval Method (2025.acl-long)
Copied to clipboard
| Challenge: | Existing RAG solutions address the alignment problem in a limited manner . ARM explores relationships among data objects, enabling a retrieve-all-at-once solution for complex queries . |
| Approach: | Experimental results show that ARM improves alignment of open-domain questions with available data . ARM explores relationships among data objects, enabling a retrieve-all-at-once solution for complex queries. |
| Outcome: | Experimental results show that ARM outperforms existing RAG methods on complex open-domain questions. |