Point at the paper, arXiv:2610.36858

README.md

@@ -19,7 +19,7 @@ trained under gradient isolation so the core never receives a forget-set gradien
 is read two ways: with the branch off it satisfies a request to delete a person's training data,
 with the branch on it restores what that data taught.
 
-Code: <https://github.com/Jingong-Chen/MoME>
+Paper: <https://arxiv.org/abs/2610.36858> · Code: <https://github.com/Jingong-Chen/MoME>
 
 ## Files
 
@@ -55,6 +55,18 @@ python eval_partition.py --config_file configs/Market/vit_transreid_stride_mome_
   --weight market/mome_core.pth --mode core
 ```
 
+## Citation
+
+```bibtex
+@article{chen2026mome,
+  title   = {Forget the Data, Keep the Capability: Switchable Unlearning for Retrieval},
+  author  = {Chen, Jingong and Gao, Kyle and Li, Guangyuan and Pack, Chulwoo and
+             Liu, Sijia and Won, Kwanghee},
+  journal = {arXiv preprint arXiv:2610.36858},
+  year    = {2026}
+}
+```
+
 ## Licence
 
 MIT, as the code is. The datasets these were trained on are not redistributed and keep the terms