Update README.md

README.md

@@ -332,7 +332,7 @@ We use the following _LLM-based metrics_:
 
 # Results
 In this section, we give the full experiment results, wherein the metrics of **Prec.**, **Rec.**, **F1.**, **R.L.**, **B.S.**, **Rel.**, **Eff.**, **Comp.**, **Pos.**, and **Avg.** represent image precision, image recall, image F1 score, rouge-l, BERTScore, image relevance, image effectiveness, comprehensive score, image position score, and average score, respectively. Specifically, the metric **Ord.** represents image ordering score. 
-## Comprehensive performance results on Wit（Wit-MQA）.
+## Comprehensive performance results on MRAMG-Wit（Web Dataset）.
 | Framework  | Model                  | MRAMG-Wit |       |       |       |       |       |       |       |       |       |
 |------------|------------------------|-----------|-------|-------|-------|-------|-------|-------|-------|-------|-------|
 |            |                        | Prec.     | Rec.  | F1    | R.L.  | B.S.  | Rel.  | Eff.  | Comp. | Pos.  | Avg.  |
@@ -396,7 +396,7 @@ In this section, we give the full experiment results, wherein the metrics of **P
 |            | Llama-3.3-70B-Instruct | 70.61     | 94.40 | 76.35 | 47.86 | 95.47 | 78.16 | 71.84 | 76.96 | 71.46 | 75.90 |
 
 ## Comprehensive performance results on MRAMG-Web（Web Dataset）.
-| Framework  | Model                  |  MRAMG-Web+ |       |       |       |       |       |       |       |       |       |
+| Framework  | Model                  |  MRAMG-Web |       |       |       |       |       |       |       |       |       |
 |------------|------------------------|-----------|-------|-------|-------|-------|-------|-------|-------|-------|-------|
 |            |                        | Prec.     | Rec.  | F1    | R.L.  | B.S.  | Rel.  | Eff.  | Comp. | Pos.  | Avg.  |
 | Rule-Based | GPT-4o                 | 32.47     | 16.93 | 22.11 | 39.17 | 90.56 | 29.47 | 27.81 | 73.87 | 32.80 | 40.58 |