Unverified50% confidenceFactExact time
The KV cache of recurrent models is highly redundant along the recurrent axis, and different recurrent steps differ greatly in their sensitivity to quantization.
1
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50%
Confidence
Long-term
Relevance
11/4/2026
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Related Claims
UnverifiedThe inequality uses only the observed cycle lengths and explicitly retains the truncation term and the effect of the cycle after the observation period ends.70% similarUnverifiedRecurrent-based models are prone to hidden state collapse and gradient instability when trained via backpropagation through time (BPTT).69% similarUnverifiedIn the ReAct loop, once the model misjudges the cause of an error, it may repeatedly try along the wrong path; long loops consume large amounts of tokens, driving up cost and latency.69% similarUnverifiedLoop机制的重试本身并不保证收敛，反而可能在每轮循环中引入新偏差，使问题空间越来越难预测68% similarUnverifiedTraditional KV cache compression methods (such as uniform bit quantization and fixed per-loop precision allocation rules) cannot allocate resources based on the actual sensitivity of each layer in each loop.67% similar
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