Unverified50% confidenceFactExact time
Historical conversations are usually truncated by turns or by a token-count window, to avoid the prompt growing indefinitely and exceeding the model's context length limit or driving up call costs.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedA longer context makes model conversations more coherent, but also consumes more tokens and may hit the model's maximum input length limit.77% similarUnverified当对话轮次过多超过Token上限时，需采用滑动窗口、摘要压缩、关键信息提取等策略管理上下文长度77% similarUnverified长对话切换至上下文窗口较小的模型时可能出现历史截断问题76% similarUnverifiedPersisting the complete conversation history in full is both inefficient and counterproductive, as lengthy history rapidly consumes the context window budget and irrelevant context degrades generation quality.72% similarUnverified开发者通常通过将历史对话拼接进上下文窗口来模拟LLM的记忆，但会遭遇上下文长度限制、成本飙升及信息检索精度下降等问题71% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1005453API
curl https://kongchang.com/api/v1/knowledge/claims/1005453MCP
get_claim(id=1005453)