Unverified50% confidenceTradeoffExact time
条件化历史帧方法的滑动窗口注意力在16帧上下文时已接近单卡显存上限,且计算量随上下文增长呈二次方增长
1
Sources
50%
Confidence
Long-term
Relevance
7/13/2026
First Seen
Sources
Related Claims
Unverified上下文窗口大小不等于有效上下文长度,超出有效注意力范围会导致遗忘漂移现象72% similarUnverified更长的上下文窗口并未消除注意力稀释效应,反而带来更高的单次调用成本71% similarVerifiedThe self-attention mechanism causes computational complexity to grow quadratically with sequence length, so expanding the context from 1,000 to 4,000 tokens increases the computation by 16 times.68% similarVerifiedEven models with a million-token context face an attention dilution problem when handling large codebases—when the context is too long, the model's attention to early content drops significantly.67% similarUnverifiedThe root cause of attention dilution lies in Softmax normalization: the more tokens in a sequence, the effective attention weight allocated to each position decreases approximately inversely proportional to the sequence length.67% similar
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