Unverified50% confidenceBenchmarkExact time
Each WOVEN training subset of about 2,000 samples improves 22 of 26 external benchmarks in total, with a maximum improvement of 27.3 percentage points.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/13/2026
First Seen
Valid until: 1/11/2027
Sources
Related Entities
Related Claims
UnverifiedOn the CNN2-with-pruning task, trainable parameters were compressed to 204, with an accuracy of 81.25%.70% similarUnverifiedFine-tuning on a few hundred real data samples on top of synthetic pre-training can often improve mAP by 10 to 20 percentage points.68% similarUnverifiedAccording to data from Artificial Analysis, the number of reasoning tokens per task doubled from approximately 42,000 in Opus 5 to 84,000 in Opus 5.5, while output tokens only increased from 30,000 to 35,000.67% similarUnverifiedThe rule of thumb given by the Chinchilla scaling law is that the number of training tokens should be approximately 20 times the number of parameters67% similarUnverifiedThe gains from increasing model parameters are approximately twice those from performing a second pass over the data.67% similar
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