<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> This repository, bansky-cl/diffusion-nlp-paper-arxiv, automatically aggregates recent research papers on diffusion models applied to Natural Language Processing (NLP) from arXiv. It serves as a dynamic feed for researchers and practitioners tracking advancements in this specialized intersection of AI, providing quick access to the latest publications.

How It Works

The repository functions as an automated curator, fetching and listing new arXiv publications related to diffusion models in NLP. It provides essential metadata such as titles, abstracts, and publication dates, enabling quick discovery of the latest research. A companion repository, "Diffusion-LM-Papers," is mentioned for more curated content, suggesting this repository's primary role is automated, broad-spectrum retrieval from arXiv.

Quick Start & Requirements

This repository is a collection of research paper links and metadata, not a software project. It requires no installation or specific runtime environment.

Highlighted Details

• Automated arXiv Aggregation: Provides a continuously updated list of diffusion NLP papers, ensuring access to the latest research.
• Focus on Diffusion NLP: Specifically targets the intersection of diffusion models and NLP, a rapidly advancing subfield.
• Metadata Rich: Includes titles, abstracts, and publication dates for efficient literature review.
• Tiered Curation: Complements a more curated repository ("Diffusion-LM-Papers") for specialized needs.

Maintenance & Community

No information is available in the provided README regarding maintenance status, contributors, or community engagement.

Licensing & Compatibility

No licensing information is provided in the README.

Limitations & Caveats

• The repository is an informational index, not a deployable tool or library.
• Content is limited to what is automatically discoverable on arXiv based on the repository's criteria.
• Deeper curation and potentially more refined content are available in a separate repository.