Spaces:
Running
on
Zero
Running
on
Zero
Commit
Β·
cb1ecf3
1
Parent(s):
00c5352
update
Browse files
app.py
CHANGED
@@ -857,7 +857,12 @@ with gr.Blocks(theme=theme, css=custom_css) as demo:
|
|
857 |
|
858 |
gr.Markdown("""
|
859 |
<div style="font-size: 18px;">
|
860 |
-
AttnTrace is an efficient context traceback method for long contexts (e.g., full papers). It is over 15Γ faster than the state-of-the-art context traceback method TracLLM. Compared to previous attention-based approaches, AttnTrace is more accurate, reliable, and memory-efficient.
|
|
|
|
|
|
|
|
|
|
|
861 |
|
862 |
- π prompt injection instructions that manipulate LLM-generated paper reviews.
|
863 |
- π» malicious comment & code hiding in the codebase that misleads the AI coding assistant.
|
|
|
857 |
|
858 |
gr.Markdown("""
|
859 |
<div style="font-size: 18px;">
|
860 |
+
AttnTrace is an efficient context traceback method for long contexts (e.g., full papers). It is over 15Γ faster than the state-of-the-art context traceback method TracLLM. Compared to previous attention-based approaches, AttnTrace is more accurate, reliable, and memory-efficient.
|
861 |
+
""", elem_classes="feature-highlights")
|
862 |
+
# Feature highlights
|
863 |
+
gr.Markdown("""
|
864 |
+
<div style="font-size: 18px;">
|
865 |
+
AttnTrace can be used in many real-world applications, such as tracing back to:
|
866 |
|
867 |
- π prompt injection instructions that manipulate LLM-generated paper reviews.
|
868 |
- π» malicious comment & code hiding in the codebase that misleads the AI coding assistant.
|