Unverified50% confidenceBenchmarkExact time
MLExpert raised the base model's average medal rate on MLE-Bench Lite from 37.9% to 72.7%.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/16/2026
First Seen
Valid until: 1/14/2027
Sources
Related Entities
Related Claims
UnverifiedIn the segment where gains exceeded +30%, average model predictions ranged from 27.3% for Claude Opus 5.5 to 61.6% for GPT-5.4 mini, while the actual rise rate was 42.8%.64% similarUnverified在SWE-bench最初公开结果中GPT-4的解决率仅约1.7%，Devin宣称达到13.86%，SWE-agent达到12.5%60% similarUnverifiedHMA achieved an any-medal rate of 78.2% on the MLE-bench benchmark (covering 75 Kaggle tasks), setting a new state-of-the-art (SOTA).60% similarUnverifiedTEMPEST outperforms the best classical model by 17.9 percentage points and the strongest triplet-loss baseline by 58.4 percentage points.59% similarUnverifiedAfter the researchers added a sentence to four models requiring them to implement "ensuring security while meeting functional requirements," GPT-5.6-Sol's functional + security pass rate rose from 24.7% to 46.2%, GLM-5.3 from 21.3% to 38.2%, Qwen3.8-Max from 22.0% to 37.6%, and DeepSeek-V4-Pro from 18.0% to 19.1%.59% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1041826API
curl https://kongchang.com/api/v1/knowledge/claims/1041826MCP
get_claim(id=1041826)