Sentence Ordering
20 papers with code • 0 benchmarks • 1 datasets
Sentence ordering task deals with finding the correct order of sentences given a randomly ordered paragraph.
Benchmarks
These leaderboards are used to track progress in Sentence Ordering
OrdinalDataset
Latest papers
Neural Sentence Ordering Based on Constraint Graphs
Our experiments on five benchmark datasets show that our method outperforms all the existing baselines significantly, achieving a new state-of-the-art performance.
On Losses for Modern Language Models
BERT set many state-of-the-art results over varied NLU benchmarks by pre-training over two tasks: masked language modelling (MLM) and next sentence prediction (NSP), the latter of which has been highly criticized.
Topological Sort for Sentence Ordering
shrimai/Topological-Sort-for-Sentence-Ordering
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ACL 2020
Sentence ordering is the task of arranging the sentences of a given text in the correct order.
Graph-based Neural Sentence Ordering
Sentence ordering is to restore the original paragraph from a set of sentences.
Partially Shuffling the Training Data to Improve Language Models
ofirpress/PartialShuffle
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arXiv 2019
Although SGD requires shuffling the training data between epochs, currently none of the word-level language modeling systems do this.
Text Coherence Analysis Based on Deep Neural Network
In this paper, we propose a novel deep coherence model (DCM) using a convolutional neural network architecture to capture the text coherence.
Sentence Ordering and Coherence Modeling using Recurrent Neural Networks
shrimai/Topological-Sort-for-Sentence-Ordering
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Modeling the structure of coherent texts is a key NLP problem.
