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ConvMemory v3: A Validity Context Layer for Conversational Memory via Target-Conditioned Relation Verification
- 用目标条件关系验证机制判断记忆是否被更新
- 在真实数据上达到98.8%的正确率，无需标签训练
- 可插拔部署，适合需要高安全性的对话系统
对话记忆检索虽优化相关性，但已过时的记忆仍可能被召回——后续对话可能已更新、修正或取代它。ConvMemory v3 引入有效性上下文层，通过目标条件关系验证检测并揭示此类更新证据，嵌套于v1/v2检索路径之后。核心机制为双证据门控：基于特定目标命题判断关系，通过MiniLM与DeBERTa-v3槽头的乘积评分（目标, 源）对，并由保守事件/操作证据进行门控。在合成多跳有效性基准上，该门控准确率达90.12% ± 1.73；通过真实数据反馈循环挖掘失败模式，仅用合成对训练，验证器成功迁移到Memora角色绑定任务，实现98.8% ± 0.9的组全正确率，且无需目标侧标签。部署层默认保留原始检索结果：上下文模式附加结构化有效性元数据，候选集与排序不变；查询条件降权模式为显式启用，适用于密集当前状态场景，使当前活跃项的H@1从基线45.1%提升至95.7% ± 1.2，同时保持非覆盖记忆99.4%召回率。六条机器可验证的安全契约约束行为。多跳图传播机制经验证有效；严格前序边的全自动构建被视为边界，因严格必要需反事实世界知识。本报告扩展ConvMemory v1（arXiv:2605.28062）和v2（arXiv:2606.10842）。
原文摘要 · Abstract (English)
Conversational memory retrieval optimizes relevance, yet a retrieved memory can be relevant and simultaneously outdated: a later turn updates, corrects, or supersedes it. ConvMemory v3 adds a validity context layer that detects and surfaces this update evidence through target-conditioned relation verification, sitting after the v1/v2 retrieval path. The core mechanism is a dual-evidence gate that conditions a relation judgment on the specific target proposition, scoring a (target, source) pair through the product of a MiniLM slot head and a DeBERTa-v3 slot head and gating it by conservative event/operation evidence. On a synthetic multi-hop validity benchmark the gate reaches 90.12% +/- 1.73 accuracy; through a real-data feedback loop that mines failure patterns but trains on synthetic pairs only, the verifier transfers to Memora role binding with zero target-side labels, reaching 98.8% +/- 0.9 group-all-correct. The deployed layer preserves retrieval by default: a context mode attaches structured validity metadata while keeping the candidate set and rank order fixed, and a query-conditioned demote mode is an explicit opt-in for dense current-state workloads, where it raises current-active H@1 from a never-demote baseline of 45.1% to 95.7% +/- 1.2 while protecting non-superseded memories at 99.4% recall. Six machine-verifiable safety contracts pin the layer's behavior. Multi-hop graph propagation is validated as a mechanism; fully automatic construction of strict prerequisite edges is characterized as a boundary, since strict necessity requires counterfactual world knowledge. This report extends ConvMemory v1 (arXiv:2605.28062) and v2 (arXiv:2606.10842).
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