README.md

metadata

title: Scientific Research Paper Summarizer
emoji: 🔬
colorFrom: indigo
colorTo: blue
sdk: gradio
python_version: 3.11
app_file: app.py
pinned: false
license: apache-2.0

🔬 Scientific Research Paper Summarizer

This Space hosts the deployment of our fine-tuned Gemma-2-2b model designed for research paper analysis and lay summarization.

Features

• Real-time Literature Fetching: Automatically searches and retrieves relevant academic papers from the arXiv repository for any entered topic.
• Intelligent Summarization: Synthesizes the core findings and key points from the retrieved literature.
• Direct References: Displays full metadata, authors, and clickable links for all source papers used during generating the overview.

How it works

1. The user inputs a research topic or question.
2. The app queries the arXiv API to fetch the most relevant papers.
3. The abstracts and titles are formatted into a template matching the model's training structure (Document:\n ... \n\nSummary:\n).
4. The fine-tuned Gemma model summarizes the core ideas.
5. Citations are displayed transparently below the response.