Update README.md

README.md

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   - [Contact](#contact)
 
 ## Overview
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 **Protap** is a benchmark dataset for evaluating protein modeling algorithms in five biologically realistic downstream applications. It enables comparative evaluation of both pre-trained models and domain-specific architectures. Protap includes both sequence and structural data, with tasks ranging from protein function prediction to targeted protein degradation.
 
-![pretrain_tasks.png](https://cdn-uploads.huggingface.co/production/uploads/6714bad02d5d8af7a0aabeb5/lhj4DJwbGD5eauN4ACNmf.png)
-![task_figure.png](https://cdn-uploads.huggingface.co/production/uploads/6714bad02d5d8af7a0aabeb5/j7YabXG-h36ywX0IH9G4q.png)
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6714bad02d5d8af7a0aabeb5/WH2f4gFfV8qv-SGPU-D0e.png)
+(I) Masked Language Modeling(MLM) is a self-supervised objective designed to recover masked residues in protein sequences;
+(II) Multi-View Contrastive Learning(MVCL) leverages protein structural information by aligning representations of biologically correlated substructures.
+(III) Protein Family Prediction(PFP) introduces functional and structural supervision by training models to predict family labels based on protein sequences and 3D structures.
 
 Protap was introduced in the paper  
 [**Protap: A Benchmark for Protein Modeling on Realistic Downstream Applications**](https://arxiv.org/abs/2506.02052)  
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 | `PLI_DAVIS` | Protein–ligand binding affinity regression            | Seq + Struct   | `test`       | `.txt`, `.json`, folder       |
 | `PROTACs`   | Ternary complex prediction in targeted degradation    | Seq + Struct   | `test`       | `.txt`, `.json`, folder       |
 
-All configurations are stored in a **token classification** format and primarily involve biological data related to proteins and molecules.
 
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