ArxivDigest: Simplifying Your Daily Research Digest
Staying current with the rapid influx of new academic papers on platforms like arXiv can be a daunting task. ArxivDigest is a project that uses advanced language models to streamline this process, offering researchers a personalized digest of newly published papers tailored to their unique interests. It effortlessly sifts through hundreds of papers to highlight the most relevant ones.
What Does ArxivDigest Offer?
ArxivDigest is designed to save researchers time by curating a list of papers based on individual research interests, as described in natural language. This list is generated and sorted by relevance using a large language model, specifically tuned for this task.
- Personalization: Researchers can specify their arXiv subject category, sub-categories, and articulate their research interests. The system then ranks the papers using relevancy scores.
- Ease of Use: Users simply need to edit a configuration file (
config.yaml) to set their preferences. - Convenient Delivery: The resulting digest can be generated in an HTML format and, with an optional setup, emailed to users daily via SendGrid. This integration requires an API key but provides a hassle-free way to receive updates.
How to Get Started
For those eager to see ArxivDigest in action, there is a demo available on Hugging Face. This does not require storing your API key, enhancing security.
- Demo Access: Visit Hugging Face, enter your OpenAI API key, and fill in your preferences to see a custom digest in action.
- Email Digests: To have digests emailed to you, create a SendGrid account and obtain an API key.
Example Configurations and Results
- Computer Science – AI and Language: Specify interests such as large language models and multimodal learning. Exclude specific applications or language-focused papers.
- Quantitative Finance focused on wealth generation, leading to a digest centered on those financial insights.
Run as a GitHub Action
To fully automate and integrate ArxivDigest into your workflow:
- Fork the repository, modify the
config.yamlfile, and configure your GitHub secrets with API keys from OpenAI and SendGrid, as well as your email settings. - Trigger actions manually or set them to run automatically.
Running Locally with a User Interface
For those preferring a GUI approach:
- Install the necessary requirements and run the local UI to preview and generate digests right on your machine.
- Securely manage your credentials using an
.envfile without exposing sensitive information.
Future Plans and Contributions
ArxivDigest continues to evolve, with plans to introduce features like content ranking by specific authors and support for open-source models. Developers are encouraged to contribute by enhancing the project with changes to the prompt, model selection, or delivery methods.
In essence, ArxivDigest is a powerful tool tailored for researchers who need to keep up with a fast-paced academic landscape, ensuring they focus on papers that matter most to their work without getting overwhelmed by volume.