Unverified50% confidenceBenchmarkExact time
Compared to baseline methods, Dude achieves improvements of up to 22.8% in recall and precision.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/5/2026
First Seen
Valid until: 12/4/2026
Sources
Related Entities
Related Claims
UnverifiedIn guided mode, the average end-to-end accuracy increased from 28.6% to 33.7%, and the ambiguity detection F1 score increased from 45.3% to 64.9%67% similarUnverifiedDGM automatically more than doubled baseline performance on the SWE-bench software engineering benchmark, achieving an absolute improvement of 30 percentage points67% similarUnverifiedDude's F1 score improves by up to 18.7%.62% similarUnverifiedEfficientNet 从 B0 到 B7，模型参数从 5.3M 增长到 66M，Top-1 精度从 77.1% 提升到 84.3%61% similarUnverifiedDevin achieved a resolution rate of 13.86% on the SWE-bench evaluation (the highest at the time).60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/860715API
curl https://kongchang.com/api/v1/knowledge/claims/860715MCP
get_claim(id=860715)