Unverified50% confidenceFactExact time
Max pooling retains only the maximum response within a local window and directly discards the information carried by the remaining pixels, leading to information loss.
1
Sources
50%
Confidence
Long-term
Relevance
8/8/2026
First Seen
Sources
谱池化详解:从频域视角重新理解CNN下采样机制
Related Claims
Unverified大模型的记忆仅限于当前上下文窗口内的token序列,对话结束后所有中间状态消失63% similarUnverifiedCurrent LLMs' memory is primarily limited by the context window, making it impossible to truly retain information across multiple independent conversations.63% similarUnverifiedEven if a model supports a context window of 128K or longer, stuffing all historical information into the prompt does not guarantee the model will correctly utilize that information, as attention dilution can cause critical information to be overlooked.62% similarUnverified寄存器溢出(Register Spilling)会将溢出变量存入本地显存,引入额外全局显存访问导致性能倒退60% similarUnverified简单的滑动窗口截断只保留最近N轮对话会导致Agent丢失早期关键信息59% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/709878API
curl https://kongchang.com/api/v1/knowledge/claims/709878MCP
get_claim(id=709878)