Update README.md

Author: vcache-project

README.md

@@ -23,7 +23,7 @@ Reliable and Efficient Semantic Prompt Caching
 
 
 
-Semantic caching reduces LLM latency and cost by returning cached model responses for semantically similar prompts (not just exact matches). **vCache** is the first verified semantic cache that **guarantees user-defined error rate bounds**. vCache replaces static thresholds with **online-learned, embedding-specific decision boundaries**—no manual fine-tuning required. This enables reliable cached response reuse across any embedding model or workload.
+vCache is the first semantic prompt cache that guarantees user-defined error rate bounds. Semantic caching reduces LLM latency and cost by returning cached model responses for semantically similar prompts (not just exact matches). vCache replaces static thresholds with **online-learned, embedding-specific decision boundaries**—no manual fine-tuning required. This enables reliable cached response reuse across any embedding model or workload.
 
 > 💳
 > **Cost & Latency Optimization** <br> 
@@ -192,4 +192,4 @@ If you use vCache for your research, please cite our [paper](https://arxiv.org/a
   journal={arXiv preprint arXiv:2502.03771},
   year={2025}
 }
-```
+```