Unverified50% confidenceFactExact time
随着对话轮次增加，每轮需携带完整历史上下文，输入token数量持续膨胀，导致推理时间呈现非线性增长
1
Sources
50%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
Related Claims
Unverified推理过程中动态增长的KV Cache会持续占用显存，长对话时可能突然触发OOM崩溃77% similarUnverified多轮对话中第N轮的输入成本是前N-1轮内容的总和，累积效应会导致成本抛物线式增长73% similarUnverified14倍的提升由多因子叠加而来：批处理贡献3-4倍、内存优化贡献1.5-2倍、会话复用与线程调优再叠加若干71% similarUnverified向量维度越高语义表达能力越强，但存储开销和检索延迟也随之增加71% similarUnverified随着多轮对话轮次增加，上下文窗口被前序对话占据，提示词中引用指令的信号强度相对下降，引用质量可能出现系统性退化70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/503612API
curl https://kongchang.com/api/v1/knowledge/claims/503612MCP
get_claim(id=503612)