# Memory-Aware and Uncertainty-Guided Retrieval for Multi-Hop Question Answering

Source: [Memory-Aware and Uncertainty-Guided Retrieval for Multi-Hop Question Answering](<https://www.sota2.com/research/paper/68fa77bf1e209131cea7513e>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T04:25:31.619Z

Authors: Yuelyu Ji, Rui Meng, Zhuochun Li, Daqing He

Published: 2025-03-29T14:27:02.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2503.23095>)

[PDF](<https://arxiv.org/pdf/2503.23095.pdf>)