Unverified50% confidenceFactExact time
In earlier tests, a rewrite that raised a tool's score from 31 to 74 instead made both models' selection performance worse.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/15/2026
First Seen
Valid until: 1/13/2027
Sources
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Related Claims
UnverifiedIn real-environment A/B testing, the post-trained checkpoint reduced the tool-call failure rate by 21.2% relatively compared to the earlier version.74% similarUnverifiedIn a two-phase coordination-proxy development comparison, both the baseline and the source-author-written candidate completed 180/180 trials; the candidate used 37.11% fewer tokens, reduced estimated endpoint cost by 33.84%, and decreased steps by 11.63%, but improvement in quality, latency, or production-environment behavior cannot be demonstrated.71% similarUnverified修复前模型每约29次下一token预测中约有1次的选择与数学上应有结果不同71% similarUnverifiedIn an experiment with a 32-expert miniature character model, when Token Choice routing had no load balancing loss, a single expert swallowed 57% of the tokens in the early stage of training, and 17 of the 32 experts were almost ignored.71% similarUnverifiedAblation analysis shows that fine-tuning on the segment paradigm yields a +5.29-point improvement on the test set, while replacing the first 4,500 transcript words with 2,000 retrieved words yields only a +1.55-point improvement.70% similar
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