Reported model / MODEL EVIDENCE

MIC2-SQL Anonymous

1 benchmarks · 1 observations · 1 sources

Scores at a glance

1 benchmarks · large dot: MIC2-SQL Anonymous; small dots: closest models where reported

Closest models by score

Similar positions on shared benchmark leaderboards. Smaller gaps are closer.

How similarity is measured

Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.

Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

  1. Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs — published result table ↗

    Li, Jinyang, Hui, Binyuan, Qu, Ge, Yang, Jiaxi, Li, Binhua, Li, Bowen et al. · 2023

    All 18 authors

    Li, Jinyang, Hui, Binyuan, Qu, Ge, Yang, Jiaxi, Li, Binhua, Li, Bowen, Wang, Bailin, Qin, Bowen, Cao, Rongyu, Geng, Ruiying, Huo, Nan, Zhou, Xuanhe, Ma, Chenhao, Li, Guoliang, Chang, Kevin C. C., Huang, Fei, Cheng, Reynold, Li, Yongbin

Names used in source tables

MIC2-SQL Anonymous