Summary of Logogramnlp: Comparing Visual and Textual Representations Of Ancient Logographic Writing Systems For Nlp, by Danlu Chen and Freda Shi and Aditi Agarwal and Jacobo Myerston and Taylor Berg-kirkpatrick
LogogramNLP: Comparing Visual and Textual Representations of Ancient Logographic Writing Systems for NLP
by Danlu Chen, Freda Shi, Aditi Agarwal, Jacobo Myerston, Taylor Berg-Kirkpatrick
First submitted to arxiv on: 8 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV)
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 The paper proposes a novel approach to process ancient logographic writing systems, which typically rely on symbolic representations. However, creating an analogous representation for these systems is labor-intensive and requires expert knowledge. The authors highlight that a significant portion of logographic data remains in visual form due to the lack of transcription, hindering researchers’ ability to apply NLP toolkits. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Ancient logographic languages are written systems that use symbols to represent words or concepts. Right now, most of these writings exist only as images, making it hard for experts to study and analyze them using modern tools like those from natural language processing (NLP). The goal of this research is to make it easier to work with these ancient writings by creating a way to turn the visual symbols into something that computers can understand. |
Keywords
» Artificial intelligence » Natural language processing » Nlp
