diff --git a/xben-benchmark-results/README.md b/xben-benchmark-results/README.md
index 7fd53c8..d768670 100644
--- a/xben-benchmark-results/README.md
+++ b/xben-benchmark-results/README.md
@@ -1,4 +1,4 @@
-# Shannon AI: Achieving 96% Success on the hint-free XBOW Benchmark
+# Achieving 96% Success on the hint-free XBOW Benchmark
 
 Shannon Lite, our open-source AI pentester, achieved a **96% success rate (100/104 exploits)** on a systematically cleaned, hint-free version of the XBOW security benchmark. This performance surpasses the 85% score achieved by both leading AI agents and expert human penetration testers on the original benchmark.
 
@@ -179,16 +179,6 @@ Shannon's production-grade workflow includes comprehensive reconnaissance and vu
 
 Additionally, Shannon's primary goal is exploit confirmation rather than CTF flag capture. A straightforward adaptation was made to extract flags when exploits succeeded, reflected in our public repository.
 
-**Performance note:** Current runtime averages 1.5 hours for the full benchmark suite. API costs range from $16-50 depending on target complexity.
-
----
-
-**Data sources:**
-
-1. [XBOW vs Humans](https://xbow.com/blog/xbow-vs-humans)
-2. [Cyber-AutoAgent Performance Analysis](https://medium.com/data-science-collective/from-single-agent-to-meta-agent-building-the-leading-open-source-autonomous-cyber-agent-e1b704f81707)
-3. [Building the Leading Open Source Pentesting Agent](https://medium.com/data-science-collective/building-the-leading-open-source-pentesting-agent-architecture-lessons-from-xbow-benchmark-f6874f932ca4)
-
 ---
 
 *Built with ❤️ by the Keygraph team*