[martin-dev] add links
Browse files- demo/launch_gradio.py +6 -3
demo/launch_gradio.py
CHANGED
|
@@ -556,11 +556,14 @@ def create_demo() -> gr.Blocks:
|
|
| 556 |
"""
|
| 557 |
with gr.Blocks(title='VLM-Lens Visualizer') as demo:
|
| 558 |
gr.Markdown("""
|
| 559 |
-
# VLM-Lens
|
| 560 |
|
| 561 |
-
|
| 562 |
-
and visualizes the probability distribution of the first token in the response for each image.
|
| 563 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 564 |
**Instructions:**
|
| 565 |
1. Select a VLM from the dropdown
|
| 566 |
2. Select a layer from the available embedding layers
|
|
|
|
| 556 |
"""
|
| 557 |
with gr.Blocks(title='VLM-Lens Visualizer') as demo:
|
| 558 |
gr.Markdown("""
|
| 559 |
+
# VLM-Lens (EMNLP 2025 System Demonstration)
|
| 560 |
|
| 561 |
+
## [arXiv](https://arxiv.org/abs/2510.02292) | [GitHub](https://github.com/compling-wat/vlm-lens)
|
|
|
|
| 562 |
|
| 563 |
+
This beta version processes an instruction with up to two images through various VLMs,
|
| 564 |
+
computes cosine similarity between their embeddings at a specified layer,
|
| 565 |
+
and visualizes the probability distribution of the first token in the response for each image.
|
| 566 |
+
|
| 567 |
**Instructions:**
|
| 568 |
1. Select a VLM from the dropdown
|
| 569 |
2. Select a layer from the available embedding layers
|