Memory-Aware and Uncertainty-Guided Retrieval for Multi-Hop Question Answering
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916665889914880 |
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| author | Ji, Yuelyu Meng, Rui Li, Zhuochun He, Daqing |
| author_facet | Ji, Yuelyu Meng, Rui Li, Zhuochun He, Daqing |
| contents | Multi-hop question answering (QA) requires models to retrieve and reason over multiple pieces of evidence. While Retrieval-Augmented Generation (RAG) has made progress in this area, existing methods often suffer from two key limitations: (1) fixed or overly frequent retrieval steps, and (2) ineffective use of previously retrieved knowledge.
We propose MIND (Memory-Informed and INteractive Dynamic RAG), a framework that addresses these challenges through: (i) prompt-based entity extraction to identify reasoning-relevant elements, (ii) dynamic retrieval triggering based on token-level entropy and attention signals, and (iii) memory-aware filtering, which stores high-confidence facts across reasoning steps to enable consistent multi-hop generation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_23095 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Memory-Aware and Uncertainty-Guided Retrieval for Multi-Hop Question Answering Ji, Yuelyu Meng, Rui Li, Zhuochun He, Daqing Computation and Language Multi-hop question answering (QA) requires models to retrieve and reason over multiple pieces of evidence. While Retrieval-Augmented Generation (RAG) has made progress in this area, existing methods often suffer from two key limitations: (1) fixed or overly frequent retrieval steps, and (2) ineffective use of previously retrieved knowledge. We propose MIND (Memory-Informed and INteractive Dynamic RAG), a framework that addresses these challenges through: (i) prompt-based entity extraction to identify reasoning-relevant elements, (ii) dynamic retrieval triggering based on token-level entropy and attention signals, and (iii) memory-aware filtering, which stores high-confidence facts across reasoning steps to enable consistent multi-hop generation. |
| title | Memory-Aware and Uncertainty-Guided Retrieval for Multi-Hop Question Answering |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2503.23095 |