An Introduction to ArXivQA: Automated Question Answering with ArXiv Papers
Overview of ArXivQA
ArXivQA is a pioneering project focused on creating an automated platform for question answering using academic papers from the ArXiv repository. As part of this initiative, the latest research papers across various fields are continually added and made available for exploration. This allows users, researchers, and enthusiasts to delve into the vast ocean of scientific literature with ease.
Latest Research Additions
The project features the latest 25 papers, each equipped with a direct link to the ArXiv page for detailed reading, as well as a link to the Question Answering (QA) section. Some intriguing papers include:
- View Selection for 3D Captioning via Diffusion Ranking: Tackling the challenge of view selection in 3D environments.
- Language Imbalance Can Boost Cross-lingual Generalisation: Exploring how language imbalance affects language models.
- OSWorld: Creating benchmarks for evaluating multimodal agents in computer environments.
Each of these papers is stored with links both to the original source on ArXiv and a curated QA file on the ArXivQA GitHub repository.
Broad Coverage Through Time
ArXivQA organizes papers by year, spanning from 2009 to the present. This chronological cataloging makes it accessible for users to find papers based on the specific year of interest, allowing for seamless tracking of progress in a particular field over time.
Acknowledgments and Support
The ArXivQA project has received generous support from Anthropic, through the provision of free access to the Claude-2.1 API. This support has been crucial in enabling ArXivQA to deliver precise and contextual question-answering capabilities.
ArXivQA emerges as an invaluable resource for those who wish to stay updated on the latest scientific advances across different disciplines. This project not only eases the access to academic knowledge but also enhances understanding by providing concise answers to complex research inquiries.