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Under review as a conference paper at ICLR 2027

QVRMem: Query-Time Validation and Reanswering for Evolving Memory

Abstract

Retrieving an update does not ensure that generated answers reflect it. We present QVRMem (Query-time Validation and Reanswering for Memory), a query-time method that separates dependency validation from question-directed reanswering. Validation checks facts that may shape the response before answer construction. For eligible queries, reanswering acquires associated records and reassesses the question using accumulated raw evidence. This readout distinguishes refuting an outdated proposition from identifying the current value, while handling applicable withdrawal requests. By retaining raw records, the method avoids generation-model token usage during memory construction. With Qwen3.5-9B, QVRMem reaches 73.00% accuracy on STALE and 38.50% on MEME's evolving-information tasks, exceeding the strongest evaluated baselines by 23.52 and 15.94 percentage points, respectively. Ablations show different strengths in stale-premise handling and state-sensitive answering. With DeepSeek-V4.1-Flash, the full method reaches 79.17% accuracy on STALE and 48.99% on MEME.

open until 14 Dec 2026

est. 32% chance this paper gets accepted at ICLR 2027.

Reject 68%Accept 32%

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