Update src/about.py
#2
by
DamonDemon
- opened
- src/about.py +17 -14
src/about.py
CHANGED
@@ -28,30 +28,33 @@ SUB_TITLE = """<h2 align="center" id="space-title">Effective and efficient adver
|
|
28 |
|
29 |
# What does your leaderboard evaluate?
|
30 |
INTRODUCTION_TEXT = """
|
31 |
-
This benchmark
|
32 |
(i.e., DMs after unlearning undesirable concepts, styles, or objects) across a variety of tasks. For more details, please visit the [project](https://www.optml-group.com/posts/mu_attack),
|
33 |
check the [code](https://github.com/OPTML-Group/Diffusion-MU-Attack), and read the [paper](https://arxiv.org/abs/2310.11868).\\
|
34 |
-
Demo of our offensive method: [UnlearnDiffAtk](https://huggingface.co/spaces/
|
35 |
-
Demo of our defensive method: [AdvUnlearn](https://huggingface.co/spaces/
|
36 |
"""
|
37 |
|
38 |
# Which evaluations are you running? how can people reproduce what you have?
|
39 |
LLM_BENCHMARKS_TEXT = f"""
|
40 |
For more details of Unlearning Methods used in this benchmarks:\\
|
41 |
-
[
|
42 |
-
[Forget-Me-Not
|
43 |
-
[
|
44 |
-
[Unified Concept Editing
|
45 |
-
[
|
|
|
|
|
|
|
|
|
46 |
"""
|
47 |
|
48 |
EVALUATION_QUEUE_TEXT = """
|
49 |
-
Evaluation Metrics:
|
50 |
-
rate (
|
51 |
-
|
52 |
-
(
|
53 |
-
(3) CLIP (Contrastive Language-Image Pretraining) Score is
|
54 |
-
the number -1 means no data reported till now
|
55 |
"""
|
56 |
|
57 |
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
|
|
|
28 |
|
29 |
# What does your leaderboard evaluate?
|
30 |
INTRODUCTION_TEXT = """
|
31 |
+
This benchmark evaluates the robustness of safety-driven unlearned diffusion models (DMs)
|
32 |
(i.e., DMs after unlearning undesirable concepts, styles, or objects) across a variety of tasks. For more details, please visit the [project](https://www.optml-group.com/posts/mu_attack),
|
33 |
check the [code](https://github.com/OPTML-Group/Diffusion-MU-Attack), and read the [paper](https://arxiv.org/abs/2310.11868).\\
|
34 |
+
Demo of our offensive method: [UnlearnDiffAtk](https://huggingface.co/spaces/Intel/UnlearnDiffAtk)\\
|
35 |
+
Demo of our defensive method: [AdvUnlearn](https://huggingface.co/spaces/Intel/AdvUnlearn)
|
36 |
"""
|
37 |
|
38 |
# Which evaluations are you running? how can people reproduce what you have?
|
39 |
LLM_BENCHMARKS_TEXT = f"""
|
40 |
For more details of Unlearning Methods used in this benchmarks:\\
|
41 |
+
(1) [Erased Stable Diffusion (ESD)](https://github.com/rohitgandikota/erasing);\\
|
42 |
+
(2) [Forget-Me-Not (FMN)](https://github.com/SHI-Labs/Forget-Me-Not);\\
|
43 |
+
(3) [Ablating Concepts (AC)](https://github.com/nupurkmr9/concept-ablation);\\
|
44 |
+
(4) [Unified Concept Editing (UCE)](https://github.com/rohitgandikota/unified-concept-editing);\\
|
45 |
+
(5) [concept-SemiPermeable Membrane (SPM)] (https://github.com/Con6924/SPM); \\
|
46 |
+
(6) [Saliency Unlearning (SalUn)] (https://github.com/OPTML-Group/Unlearn-Saliency); \\
|
47 |
+
(7) [EraseDiff (ED)] (https://github.com/JingWu321/EraseDiff)
|
48 |
+
(8) [ScissorHands (SH)] (https://github.com/JingWu321/Scissorhands)
|
49 |
+
|
50 |
"""
|
51 |
|
52 |
EVALUATION_QUEUE_TEXT = """
|
53 |
+
Evaluation Metrics: \\
|
54 |
+
(1) Pre-attack success rate (pre-ASR), lower is better; \\
|
55 |
+
(2) Post-attack success rate (post-ASR), lower is better; \\
|
56 |
+
(3) Fréchet inception distance(FID) of images generated by Unlearned Methods, lower is better; \\
|
57 |
+
(3) CLIP (Contrastive Language-Image Pretraining) Score is to measure contextual alignment with prompt descriptions, higher is better.
|
|
|
58 |
"""
|
59 |
|
60 |
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
|