ICLR 2025 Paper Finder

This is a simple terminal-based tool for finding relevant papers from ICLR 2025 using semantic search.

It uses:

• intfloat/e5-large-v2, an open-source embedding model
• faiss for efficient vector similarity search
• Paper data extracted from the OpenReview API

Getting Started

1. Clone the repository

2. Create and activate a virtual environment

python -m venv env
source env/bin/activate 

3. Install dependencies

pip install -r requirements.txt

4. Run the script

python find_papers.py

It may take some time to load the model the first time. Once loaded, you can enter queries in the terminal.

Features

• Displays title, authors, and a direct link to the paper.
• Optional flags:
  • --abstract to show abstracts
  • --spotlight to filter only spotlight papers
  • --number=20 to control the number of returned results (default is 10)

Example: Query: multimodal models --abstract --spotlight --number=15