Unverified50% confidenceFactExact time
The possible causes of memory system failure are distributed across five stages: whether information was correctly saved, whether the correct information was retrieved from FalkorDB, whether the backend passed the retrieved information to the model, whether the model had enough context to understand the associations, and whether the model ignored or misread the information it received.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
Unverified混淆情节记忆与语义记忆的存储介质是常见架构错误:将需精确检索的任务状态放入向量库会引入近似误差,将需语义检索的知识放入关系数据库会导致召回率低下74% similarUnverifiedIf the memory store is full of duplicate, outdated, or mutually contradictory entries, the retrieval results will contain large amounts of low-value information, crowding out context space and even misleading the model, which is context pollution.72% similarUnverifiedIn multi-step agentic systems based on LangGraph, abnormal intermediate steps, tool call failures, or unexpected model outputs may cause incomplete or incorrect data to be written into the memory state, which is known as state contamination.70% similarUnverifiedHard-coding the use of the file system for memory persistence in the prompt limits the model's ability to explore other solutions such as vector databases, structured databases, and knowledge graphs.70% similarUnverifiedIf incorrect information is saved to long-term memory, it will contaminate subsequent tasks; only truly valuable, confirmed information should be saved.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1060571API
curl https://kongchang.com/api/v1/knowledge/claims/1060571MCP
get_claim(id=1060571)