Update README.md

README.md

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 **Anonymous Open Source now**
 
-This repo provids the training data and evaluation data for MolParser, proposed in paper *“MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild“*
+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)
 
 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.
 
 * MolParser-Pretrain: More than 7.7M synthetic training data in `pretrain_synthetic_7M` subset;
 
-* MolParser-SFT [WIP]: Nearly 400k samples for fine-tuning stage. (We have identified some annotation errors and are currently re-cleaning the data. Once completed, we will partially open-source it.)
+* 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-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-20k Benchmark [WIP]: 20k molecule structure images cropped from real patents or paper `test_simple_10k`（ordinary）subset and `test_markush_10k`（markush）subset; (We have identified some annotation errors, we will update the version)
+* 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;
 
 As the paper is still **under review**, this data is provided **anonymously**. More information will be provided after the paper has been accepted.