Unverified50% confidenceFactExact time
The FilterFusion network itself has a computational cost of 0.18 GFLOPs.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/16/2026
First Seen
Valid until: 1/14/2027
Sources
Related Entities
Related Claims
UnverifiedGFLOPs is a commonly used unit for measuring the computational cost of neural network inference, and 0.18 GFLOPs means a single frame requires only about 180 million floating-point operations.64% similarUnverifiedAt small scale, the FLOPs share of the MLP layer is approximately 44%, rising to approximately 80% when scaled to 175B parameters56% similarUnverifiedResNet-50 has 25 million parameters and 4 GFLOPs of computation.56% similarUnverifiedRaw drift magnitude cannot predict few-shot success or failure (correlation coefficient r=0.20), whereas content delta can effectively predict it (Spearman correlation rho=+0.65, p=0.043).55% similarUnverifiedThe GLM-OCR model has 0.9B (900 million) parameters.55% similar
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