Remove citation info

README.md

@@ -16,7 +16,7 @@ task_categories:
 pretty_name: Mirage 18k Dataset
 ---
 
-# Mirage 18k: Dataset for Glass Segmentation & Depth Estimation
+# [IROS 2026] Mirage 18k: Dataset for Glass Segmentation & Depth Estimation
 
 **Mirage 18k** is a novel, multi-task dataset comprising **18,353 manually annotated images** across **38 unique indoor scenes**, designed specifically for joint glass segmentation and glass-aware monocular depth estimation in robotics.
 
@@ -27,6 +27,8 @@ It contains diverse real-world glass structures (indoor panes, frosted doors, wi
 * **Project Page:** [silica-mirage.github.io](https://silica-mirage.github.io/)
 * **Example Data:** [GitHub `example/` Directory](https://github.com/rtarun1/Silica/tree/main/example)
 
+This work has been accepted for publication at IROS 2026, as part of the work _SILICA: Repurposing Diffusion Priors for Joint Glass Segmentation and Depth Estimation_.
+
 ---
 
 ## Dataset Acquisition & Overview
@@ -85,19 +87,3 @@ To guarantee strict out-of-distribution evaluation, scenes included in test spli
 
 **Quick Test:** To run quick standalone inference on a sample subset without downloading the full dataset, check out the sample images, raw depth, and camera intrinsic files available directly in our [GitHub `example/` folder](https://github.com/rtarun1/Silica/tree/master/example).
 
-
----
-
-## Citation
-
-If you use the Mirage 18k dataset in your research, please cite:
-
-```bibtex
-@inproceedings{tarun2026silica,
-  title={SILICA: Repurposing Diffusion Priors for Joint Glass Segmentation and Depth Estimation},
-  author={R., Tarun and Verma, Anuj and Nanwani, Laksh and Garg, Sourav and Krishna, K. Madhava},
-  booktitle={IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
-  year={2026},
-  note={Accepted for publication}
-}
-```