Autocorrection of arabic common errors for large text corpus

Toward autocorrection of chemical process flowsheets using large language models

The process engineering domain widely uses Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (P&IDs) to represent process flows and equipment configurations. However, the P&IDs and PFDs, hereafter cal…

MedAutoCorrect: Image-Conditioned Autocorrection in Medical Reporting

In medical reporting, the accuracy of radiological reports, whether generated by humans or machine learning algorithms, is critical. We tackle a new task in this paper: image-conditioned autocorrection of inaccuracies wi…

Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs

A piping and instrumentation diagram (P&ID) is a central reference document in chemical process engineering. Currently, chemical engineers manually review P&IDs through visual inspection to find and rectify errors. Howev…

Autonomous Self-Assessment of Autocorrections: Exploring Text Message Dialogues

Is it Great or Terrible? Preserving Sentiment in Neural Machine Translation of Arabic Reviews

Since the advent of Neural Machine Translation (NMT) approaches there has been a tremendous improvement in the quality of automatic translation. However, NMT output still lacks accuracy in some low-resource languages and…