Loading Now

Summary of Medit: Multilingual Text Editing Via Instruction Tuning, by Vipul Raheja and Dimitris Alikaniotis and Vivek Kulkarni and Bashar Alhafni and Dhruv Kumar


mEdIT: Multilingual Text Editing via Instruction Tuning

by Vipul Raheja, Dimitris Alikaniotis, Vivek Kulkarni, Bashar Alhafni, Dhruv Kumar

First submitted to arxiv on: 26 Feb 2024

Categories

  • Main: Computation and Language (cs.CL)
  • Secondary: Artificial Intelligence (cs.AI)

     Abstract of paper      PDF of paper


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 mEdIT model is a multi-lingual text editing system that can assist with tasks such as grammar correction, simplification, and paraphrasing in various languages. It’s based on large pre-trained language models that are fine-tuned using instruction tuning to take user-inputted instructions in natural language. The model is trained on multiple human-annotated datasets for three text editing tasks across six different language families. mEdIT outperforms other multilingual models on various benchmarks and generalizes well to new languages, making it a strong tool for multilingual writing assistance.
Low GrooveSquid.com (original content) Low Difficulty Summary
mEdIT is a special kind of computer program that helps people write texts in many different languages. It can correct grammar mistakes, make complex sentences simpler, and even rewrite whole paragraphs. To do this, the program uses very large collections of text from all around the world to learn how language works. When someone asks mEdIT to help with a specific task, like fixing a sentence that’s hard to understand, it uses what it learned to make changes and improve the writing.

Keywords

» Artificial intelligence  » Instruction tuning