utils/full_lb.csv

Rank,Model,Dataset,Method,Factual,Reasoning,Summary,Avg Acc,Token
1,DeepSeek-V3,MuSiQue,NaiveRAG,11.1,28.3,29.4,26.4,13k
2,DeepSeek-V3,MuSiQue,GraphRAG,90.2,22.5,20.6,30.3,9k
3,DeepSeek-V3,MuSiQue,HybridRAG,83.7,32.8,30.2,38.6,22k
4,DeepSeek-V3,MuSiQue,IterativeRAG,10.3,21.8,21.2,20.4,20k
5,DeepSeek-V3,QuALITY,NaiveRAG,83.7,33.8,17.0,48.8,50k
6,DeepSeek-V3,QuALITY,GraphRAG,70.7,20.4,19.8,39.3,50k
7,DeepSeek-V3,QuALITY,HybridRAG,80.0,20.4,14.8,41.6,99k
8,DeepSeek-V3,QuALITY,IterativeRAG,67.0,17.1,16.2,35.8,21k
9,DeepSeek-V3,Legal,NaiveRAG,54.9,11.2,39.1,32.2,46k
10,DeepSeek-V3,Legal,GraphRAG,61.6,6.7,29.1,29.3,184k
11,DeepSeek-V3,Legal,HybridRAG,72.2,11.8,34.6,36.1,230k
12,DeepSeek-V3,Legal,IterativeRAG,49.5,12.4,30.4,28.5,20k
13,DeepSeek-V3,Medical,NaiveRAG,63.1,63.5,49.1,61.1,51k
14,DeepSeek-V3,Medical,GraphRAG,55.0,56.0,43.6,53.5,38k
15,DeepSeek-V3,Medical,HybridRAG,67.8,64.0,54.0,64.7,74k
16,DeepSeek-V3,Medical,IterativeRAG,62.1,67.8,56.1,62.7,7k
17,LLaMA-3.1-8B,MuSiQue,NaiveRAG,10.3,7.9,12.0,8.6,13k
18,LLaMA-3.1-8B,MuSiQue,GraphRAG,84.4,9.7,11.4,18.7,9k
19,LLaMA-3.1-8B,MuSiQue,HybridRAG,79.9,12.1,13.9,20.3,22k
20,LLaMA-3.1-8B,MuSiQue,IterativeRAG,12.3,6.0,6.8,6.8,20k
21,LLaMA-3.1-8B,QuALITY,NaiveRAG,69.2,10.9,1.4,30.7,50k
22,LLaMA-3.1-8B,QuALITY,GraphRAG,44.7,9.5,2.5,21.2,50k
23,LLaMA-3.1-8B,QuALITY,HybridRAG,70.3,15.6,2.5,33.2,99k
24,LLaMA-3.1-8B,QuALITY,IterativeRAG,62.3,11.5,1.4,28.4,21k
25,LLaMA-3.1-8B,Legal,NaiveRAG,50.3,10.7,22.8,25.8,46k
26,LLaMA-3.1-8B,Legal,GraphRAG,55.4,7.4,19.7,25.0,184k
27,LLaMA-3.1-8B,Legal,HybridRAG,63.8,13.1,24.2,31.1,230k
28,LLaMA-3.1-8B,Legal,IterativeRAG,48.7,10.1,12.6,22.0,20k
29,LLaMA-3.1-8B,Medical,NaiveRAG,52.1,37.9,30.1,44.9,51k
30,LLaMA-3.1-8B,Medical,GraphRAG,48.1,33.6,31.8,41.7,38k
31,LLaMA-3.1-8B,Medical,HybridRAG,55.7,39.9,33.9,48.2,74k
32,LLaMA-3.1-8B,Medical,IterativeRAG,47.5,44.6,27.3,43.6,7k