Papers with multi-hop queries
Tagging-Augmented Generation: Assisting Language Models in Finding Intricate Knowledge In Long Contexts (2025.emnlp-industry)
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Anwesan Pal, Karen Hovsepian, Tinghao Guo, Mengnan Zhao, Somendra Tripathi, Nikos Kanakaris, George Mihaila, Sumit Nigam
| Challenge: | Recent studies into effective context lengths of flagship large language models (LLMs) have revealed major limitations in effective question answering (QA) and reasoning over long and complex contexts for even the largest and most impressive cadre of models. |
| Approach: | They propose a lightweight data augmentation strategy that boosts LLM performance in long-context scenarios without degrading and altering the integrity and composition of retrieved documents. |
| Outcome: | The proposed strategy boosts performance in long-context scenarios without degrading and altering the integrity and composition of retrieved documents. |
Breaking the Static Graph: Context-Aware Traversal for Graph-Based RAG (2026.findings-acl)
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| Challenge: | Recent advances in RAG focus on capturing multi-hop dependencies, but static Graphs fail to retrieve complete evidence chain. |
| Approach: | They propose a structure-aware approach to capture multi-hop dependencies using Knowledge Graphs and Personalized PageRank to capture semantic drift. |
| Outcome: | Experiments show that CatRAG outperforms state-of-the-art approaches . the proposed approach achieves substantial improvements in reasoning completeness . |