Summary of Docsynthv2: a Practical Autoregressive Modeling For Document Generation, by Sanket Biswas et al.
DocSynthv2: A Practical Autoregressive Modeling for Document Generation
by Sanket Biswas, Rajiv Jain, Vlad I. Morariu, Jiuxiang Gu, Puneet Mathur, Curtis Wigington, Tong Sun, Josep Lladós
First submitted to arxiv on: 12 Jun 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel approach called DocSynthv2 proposes a simple yet effective autoregressive structured model for comprehensive document generation, integrating both layout and textual cues. Unlike existing layout-generation approaches, this model focuses on the relationship between structural elements and textual content within documents to generate cohesive and contextually relevant documents without visual components. Experimental studies demonstrate enhanced generation quality and relevance through combining layout and textual information. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way of generating documents is being developed. Instead of just creating a layout, this method also considers what will be written in the document. This makes the generated documents more meaningful and related to their context. The approach uses a type of model called an autoregressive structured model. This allows it to generate documents that are well-structured and make sense. |
Keywords
» Artificial intelligence » Autoregressive
