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Found 4 papers, 2 papers with code
PEaCE: A Chemistry-Oriented Dataset for Optical Character Recognition on Scientific Documents
To mitigate this gap, we present the Printed English and Chemical Equations (PEaCE) dataset, containing both synthetic and real-world records, and evaluate the efficacy of transformer-based OCR models when trained on this resource.
Optical Character Recognition
Optical Character Recognition (OCR)
Leveraging External Knowledge Resources to Enable Domain-Specific Comprehension
Machine Reading Comprehension (MRC) has been a long-standing problem in NLP and, with the recent introduction of the BERT family of transformer based language models, it has come a long way to getting solved.
Quality > Quantity: Synthetic Corpora from Foundation Models for Closed-Domain Extractive Question Answering
Domain adaptation, the process of training a model in one domain and applying it to another, has been extensively explored in machine learning.
Learning To Describe Player Form in The MLB
Major League Baseball (MLB) has a storied history of using statistics to better understand and discuss the game of baseball, with an entire discipline of statistics dedicated to the craft, known as sabermetrics.
