Add reference to two papers (2025) in README

README.md

@@ -58,6 +58,7 @@
 | Srivatsan et al. | [STEREO: A Two-Stage Framework for Adversarially Robust Concept Erasing from Text-to-Image Diffusion Models](https://openaccess.thecvf.com/content/CVPR2025/html/Srivatsan_STEREO_A_Two-Stage_Framework_for_Adversarially_Robust_Concept_Erasing_from_CVPR_2025_paper.html)|CVPR|
 | Lee et al.          | [Localized Concept Erasure for Text-to-Image Diffusion Models Using Training-Free Gated Low-Rank Adaptation](https://openaccess.thecvf.com/content/CVPR2025/html/Lee_Localized_Concept_Erasure_for_Text-to-Image_Diffusion_Models_Using_Training-Free_Gated_CVPR_2025_paper.html)                                | CVPR                                                 |
 |Shirkavand et al. | [Efficient Fine-Tuning and Concept Suppression for Pruned Diffusion Models](https://openaccess.thecvf.com/content/CVPR2025/html/Shirkavand_Efficient_Fine-Tuning_and_Concept_Suppression_for_Pruned_Diffusion_Models_CVPR_2025_paper.html)|CVPR|
+| Spartalis et al. | [LoTUS: Large-Scale Machine Unlearning with a Taste of Uncertainty](https://cvpr.thecvf.com/virtual/2025/poster/33292) | CVPR |
 | Pan et al.          | [Multi-Objective Large Language Model Unlearning](https://ieeexplore.ieee.org/abstract/document/10889776)                                                                                                                                                                                                        | ICASSP                                               |
 | Wang et al.         | [Large Scale Knowledge Washing](https://openreview.net/forum?id=dXCpPgjTtd)                                                                                                                                                                                                                                      | ICLR                                                 |
 |Koulischer et al. |[Dynamic Negative Guidance of Diffusion Models](https://openreview.net/forum?id=6p74UyAdLa)|ICLR|
@@ -114,6 +115,7 @@
 | Sanga et al.        | [Train Once, Forget Precisely: Anchored Optimization for Efficient Post-Hoc Unlearning](https://arxiv.org/abs/2506.14515)                                                                                                                                                                                        | ICML Workshop                                        |
 | Wu et al.           | [Evaluating Deep Unlearning in Large Language Models](https://openreview.net/forum?id=376xPmmHoV)                                                                                                                                                                                                                | ICML Workshop                                        |
 | Spohn et al.        | [Align-then-Unlearn: Embedding Alignment for LLM Unlearning](https://arxiv.org/abs/2506.13181)                                                                                                                                                                                                                   | ICML Workshop                                        |
+| Spartalis et al. | [Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI](https://openreview.net/forum?id=rWc530VQE6&noteId=rWc530VQE6) | ICML Workshop |
 | Dosajh et al.       | [Unlearning Factual Knowledge from LLMs Using Adaptive RMU](https://arxiv.org/abs/2506.16548)                                                                                                                                                                                                                    | SemEval                                              |
 | Xu et al.           | [Unlearning via Model Merging](https://arxiv.org/abs/2503.21088)                                                                                                                                                                                                                                                 | SemEval                                              |
 | Bronec et al.       | [Low-Rank Negative Preference Optimization](https://arxiv.org/abs/2503.13690)                                                                                                                                                                                                                                    | SemEval                                              |