Update README.md

README.md

@@ -18,10 +18,8 @@ Spatial reasoning is important for a wide range of applications such as navigati
 analysis. Many smaller LLMs, while strong in general reasoning, often lack the ability to interpret
 spatial relationships with precision or utilize real-world geographic data effectively. For example, they
 struggle to answer queries like “What’s between Point A and Point B?” or “Find me the fastest route
-avoiding traffic at 8 AM tomorrow.” I came across this limitation through my work, in which I am
-working on prompt engineering for an LLM project that has agentic behavior in calling a geocoding
-API. Even when the LLM has access to geospatial information, smaller models struggled to correctly
-interpret user questions, so we had to switch to a much newer and larger model. 
+avoiding traffic at 8 AM tomorrow.” Even when the LLM has access to geospatial information, smaller models struggle to correctly
+interpret user questions.
 
 ## Related Work/Gap Analysis