I’ve been fascinated by AI research and its applications for a while now. Recently, I decided to take matters into my own hands and create a tool to search papers from selected AI venues. This tool uses a language model as its backbone, allowing users to query papers using their titles, keywords, or even abstracts. Yes, you read that right – abstracts! It’s surprisingly accurate.
I’ve hosted the tool on both my personal server and Hugging Face, so you can access it from either place. You can find the links to the project in my GitHub repository: https://github.com/wenhangao21/ICLR26_Paper_Finder
But why did I create this tool? Well, as an AI enthusiast, I often find myself digging through research papers to stay up-to-date with the latest developments. It can be a tedious and time-consuming process, especially when searching for specific topics or authors. That’s where my tool comes in – to make searching AI papers a breeze.
I’d love to hear your thoughts and feedback on this project. Have you ever struggled with searching through research papers? How do you currently approach it? Let me know in the comments below!
If you’re interested in exploring more AI-related projects, I’ve included a link to a podcast episode that covers some fascinating topics in the field. It’s a great way to stay informed and engaged with the AI community.
Thanks for reading, and happy searching!