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Found 7 papers, 3 papers with code
ICDAR 2021 Competition on Scientific Literature Parsing
Scientific literature contain important information related to cutting-edge innovations in diverse domains.
Grey-box Adversarial Attack And Defence For Sentiment Classification
We introduce a grey-box adversarial attack and defence framework for sentiment classification.
Global Table Extractor (GTE): A Framework for Joint Table Identification and Cell Structure Recognition Using Visual Context
With GTE-Table, we invent a new penalty based on the natural cell containment constraint of tables to train our table network aided by cell location predictions.
Elephant in the Room: An Evaluation Framework for Assessing Adversarial Examples in NLP
An adversarial example is an input transformed by small perturbations that machine learning models consistently misclassify.
Image-based table recognition: data, model, and evaluation
In addition, we propose a new Tree-Edit-Distance-based Similarity (TEDS) metric for table recognition, which more appropriately captures multi-hop cell misalignment and OCR errors than the pre-established metric.
Ranked #10 on
Table Recognition
on PubTabNet
Information Retrieval
Optical Character Recognition (OCR)
+2
Global Locality in Biomedical Relation and Event Extraction
Due to the exponential growth of biomedical literature, event and relation extraction are important tasks in biomedical text mining.
PubLayNet: largest dataset ever for document layout analysis
Deep neural networks that are developed for computer vision have been proven to be an effective method to analyze layout of document images.
Ranked #11 on
Document Layout Analysis
on PubLayNet val
