Update README.md

README.md

@@ -101,11 +101,11 @@ but without explicitly answering the query or suggesting a solution.
 
 Extract:
 
-- **Buffer A**: 10-15 words from the Top-5 ranked documents and the query itself, strongly associated with the query.
+- **Buffer A**: 10-15 words from the Top-5 ranked documents and query itself, strongly associated with the query.
 
 **Generate an adversarial sentences** that satisfy ALL the following:
 
-- Include a combination of words (at least 5) or similar words (similar embedding) from Buffer A** that is most related to the query and help promote ranking significantly and integrates well with Target Document
+- Include combination of words (at least 5) or similar words (similar embedding) from Buffer A** that is most related to the query and help promote ranking significantly and integrates well with Target Document
 - DO NOT use the words that answer the query.
 - Are **fluent**, **grammatically sound**, and **consistent with the style** of the Target Document.
 - **Do NOT answer, suggest, or hint at an answer to the Target Query**.
@@ -200,6 +200,10 @@ The following summarizes attack performance and content fidelity metrics for CRA
 | CRAFT_Qwen3          | **100.0** |  15.3† |  57.1† |  911.5† |   0.8  |    19.1 |    19.1 |    1.0  |
 | CRAFT_Llama3.3       | **100.0** | **22.2**† | **70.5**† | **940.5**† |   0.8  |    19.7 |    19.7 |    1.0  |
 
+Figure: Attack methods performance vs. detection pass rate
+
+![Attack methods performance vs detection pass](attack_methods_performance_vs_detection_pass.png)
+
 ## Dataset
 
 This model was fine-tuned using data from the following repository: