Update README.md

README.md

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 # MolParser-7M
 
-**Anonymous Open Source now**
+[**Demo**](https://ocsr.dp.tech/) | [**Paper**](https://arxiv.org/abs/2411.11098)
 
-This repo provides the training data and evaluation data for MolParser, proposed in paper *“MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild“* (ICCV2025 under review)
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+This repo provides the training data and evaluation data for MolParser, proposed in paper *“MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild“* (ICCV2025 accept)
 
 MolParser-7M contains nearly 8 million paired image-SMILES data. It should be noted that the caption of image is our extended-SMILES format, which suggested in our paper.
 
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 The following dataset will be updated with a new version, stay tuned:
 
-* **MolParser-SFT [WIP]**: Nearly 400k samples for fine-tuning stage in `sft_real` subset. (We are organizing an OCSR competition based on MolParser-7M, so we have reserved part of the MolParser-SFT data for the competition. Stay tuned!)
+* **MolParser-SFT**: Nearly 400k samples for fine-tuning stage in `sft_real` subset. (We are organizing an OCSR competition based on MolParser-7M, so we have reserved part of the MolParser-SFT data for the competition. Stay tuned!)
 
 * **MolParser-Val**: A small validation set carefully selected in-the-wild in `valid` subset. It can be used to quickly valid the model ability during the training process;
 
 * **WildMol Benchmark**: 20k molecule structure images cropped from real patents or paper, `test_simple_10k`（WildMol-10k）subset and `test_markush_10k`（WildMol-10k-M）subset;
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-As the paper is still **under review**, this data is provided **anonymously**. More information will be provided after the paper has been accepted.
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-In the future, we will continue to re-clean this dataset, open-source more data, update model checkpoints, refresh the benchmark results, and release the training code.
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-[**Anonymous Demo: Click Here**](http://101.126.35.171:50008/)