Add pipeline tag and update paper link

README.md

@@ -1,15 +1,17 @@
 ---
 license: mit
+pipeline_tag: text-classification
 ---
 
-# BarcodeMamba for Taxonomic Classification
+# BarcodeMamba+: Advancing State-Space Models for Fungal Biodiversity Research
 
-A performant and efficient Mamba-2-based foundation model for DNA barcodes in biodiversity analysis.
+BarcodeMamba+ is a foundation model for fungal barcode classification, built on a powerful and efficient state-space model architecture. It addresses critical challenges in fungal taxonomic classification, such as sparse labelling and long-tailed taxa distributions, by employing a pretrain and fine-tune paradigm. The model integrates various enhancements, including hierarchical label smoothing, a weighted loss function, and a multi-head output layer, to achieve significant performance gains over traditional supervised methods.
 
-- Check out our [paper](https://openreview.net/forum?id=6ohFEFTr10)
+- Check out our [paper](https://huggingface.co/papers/2512.15931)
+- Check out our [code](https://github.com/bioscan-ml/BarcodeMamba)
 - Check out our [poster](https://neurips.cc/media/PosterPDFs/NeurIPS%202024/105938.png)
 
-# Usage 
+# Usage
 The pretrained models can be used for both taxonomic classification on seen species (fine-tune & linear probe) and making genus-level predictions on unseen species (1-NN probe). The instructions for using our models can be found at our [GitHub repository](https://github.com/bioscan-ml/BarcodeMamba).
 
 # Citation
@@ -25,4 +27,4 @@ booktitle={{NeurIPS} 2024 Workshop on Foundation Models for Science: Progress, O
 year={2024},
 url={https://openreview.net/forum?id=6ohFEFTr10}
 }
-```
+```