Unverified50% confidenceFactExact time
Residual amortization error under rare settings cannot be eliminated by simply scaling up the model.
1
Sources
50%
Confidence
Long-term
Relevance
10/12/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedSetting the deduplication granularity too strictly causes valuable nuanced differences to be mistakenly flagged as duplicates, while setting it too loosely fails to genuinely resolve redundancy — this is a product trade-off.78% similarUnverifiedSwitching to a better metric cannot salvage an analysis that already contains arbitrariness at the data construction stage.75% similarUnverifiedVRAM fragmentation can cause large tensor allocation to fail with an OOM error even when the total remaining VRAM is sufficient, because no contiguous block of adequate size can be found.71% similarUnverifiedThe slow decline in divergence is traced to the smoothing of rare contexts, as increasing the amount of data cannot effectively reduce sampling variance in sparse regions.71% similarUnverifiedThis approximation error is independent of model capacity: even with a perfect marginal distribution predictor trained on infinite data, the product approximation will inevitably deviate from the joint distribution when writing to multiple positions with dependencies in parallel.71% similar
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