Unverified50% confidenceBenchmarkExact time
Evaluated on ten multi-objective molecular optimization tasks, GeLLM³O-MFG achieved an average success rate of 81.50% under similarity constraints, significantly outperforming the base model GeLLM³O's 70.81%.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/14/2026
First Seen
Valid until: 1/12/2027
Sources
Related Entities
Related Claims
UnverifiedThe task success rates of three frontier models are very close, all falling between 84% and 89%.66% similarUnverified研究表明经过良好校准的LLM裁判与人工标注的一致性可达80%以上64% similarUnverified在Spider基准上，早期单模型方案准确率约为70%，GPT-4等大模型将其提升到80%以上，多智能体协作策略的系统已能达到85%甚至更高的执行准确率63% similarUnverifiedIn reaction optimization tasks, RSI-Anything achieved an average best-observed yield of 96.15% under a budget of 40 experiments, outperforming Bayesian optimization's 82.16%62% similarUnverifiedOn a test set of 915 compounds, SpecOpt improved the target-off-target binding gap for 84.8% of the compounds.61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1027456API
curl https://kongchang.com/api/v1/knowledge/claims/1027456MCP
get_claim(id=1027456)