Update README.md

README.md

@@ -11,15 +11,7 @@ DeepRetrieval is a novel approach that uses reinforcement learning (RL) to train
 - **Reasoning-Enhanced Generation**: Incorporates a structured generation method with explicit reasoning before query formulation
 - **State-of-the-Art Performance**: Achieves remarkable results across diverse retrieval tasks
 - **Parameter Efficiency**: With just 3B parameters, outperforms much larger models like GPT-4o and Claude-3.5-Sonnet
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-## Performance Highlights
-
-- **Literature Search**: Doubles the recall on PubMed (65.07% vs previous SOTA 24.68%) and ClinicalTrials.gov (63.18% vs previous SOTA 32.11%)
-- **Evidence-Seeking Retrieval**: Achieves performance equivalent to industry-leading LLMs on NQ and TriviaQA, and significantly outperforms them on SQuAD
-- **Classic IR**: Shows superior performance across diverse retrieval benchmarks
-- **SQL Database Search**: Excels in text-to-SQL generation for database search
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-
+- 
 ## About
 
-DeepRetrieval was developed by researchers from the University of Illinois Urbana-Champaign. For more information, visit the [GitHub repository](https://github.com/pat-jj/DeepRetrieval).
+DeepRetrieval was developed by researchers from the UIUC CS. For more information, visit the [GitHub repository](https://github.com/pat-jj/DeepRetrieval).