Summary of Deciphering the Underserved: Benchmarking Llm Ocr For Low-resource Scripts, by Muhammad Abdullah Sohail et al.
Deciphering the Underserved: Benchmarking LLM OCR for Low-Resource Scripts
by Muhammad Abdullah Sohail, Salaar Masood, Hamza Iqbal
First submitted to arxiv on: 20 Dec 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Computer Vision and Pattern Recognition (cs.CV); Image and Video Processing (eess.IV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Medium Difficulty summary: This study explores the capabilities of Large Language Models (LLMs), particularly GPT-4o, in Optical Character Recognition (OCR) tasks for low-resource scripts such as Urdu, Albanian, and Tajik. The researchers created a curated dataset with controlled variations to simulate real-world challenges. Results show that zero-shot LLM-based OCR has limitations, especially for linguistically complex scripts, highlighting the need for annotated datasets and fine-tuned models. This work emphasizes the importance of addressing accessibility gaps in text digitization, paving the way for inclusive and robust OCR solutions for underserved languages. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Low Difficulty summary: Researchers are trying to improve computer’s ability to read printed texts written in different scripts like Urdu or Albanian. They’re testing a special type of artificial intelligence called Large Language Models (LLMs) that can recognize characters on their own. The team created a dataset with pictures of text and made changes to make it more challenging, just like real-world scenarios. The results show that the LLMs have trouble recognizing texts in languages that are hard to read or write. This means we need better training data and models that can adapt to different scripts. The goal is to make reading machines more accessible and helpful for people who speak languages that aren’t as widely used. |
Keywords
» Artificial intelligence » Gpt » Zero shot
