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
Most implemented papers
Local and Global Context-Based Pairwise Models for Sentence Ordering
ruskinmanku/pairwisemodels4so
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Analysis of the two proposed decoding strategies helps better explain error propagation in pairwise models.
Improving Graph-based Sentence Ordering with Iteratively Predicted Pairwise Orderings
deeplearnxmu/irseg
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EMNLP 2021
Dominant sentence ordering models can be classified into pairwise ordering models and set-to-sequence models.
PhysNLU: A Language Resource for Evaluating Natural Language Understanding and Explanation Coherence in Physics
In order for language models to aid physics research, they must first encode representations of mathematical and natural language discourse which lead to coherent explanations, with correct ordering and relevance of statements.
Positional Diffusion: Ordering Unordered Sets with Diffusion Probabilistic Models
IIT-PAVIS/Positional_Diffusion
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We present Positional Diffusion, a plug-and-play graph formulation with Diffusion Probabilistic Models to address positional reasoning.
Reading Order Matters: Information Extraction from Visually-rich Documents by Token Path Prediction
However, BIO-tagging scheme relies on the correct order of model inputs, which is not guaranteed in real-world NER on scanned VrDs where text are recognized and arranged by OCR systems.
Non-Autoregressive Sentence Ordering
steven640pixel/nonautoregressive-sentence-ordering
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Existing sentence ordering approaches generally employ encoder-decoder frameworks with the pointer net to recover the coherence by recurrently predicting each sentence step-by-step.
Are Large Language Models Temporally Grounded?
Instead, we provide LLMs with textual narratives and probe them with respect to their common-sense knowledge of the structure and duration of events, their ability to order events along a timeline, and self-consistency within their temporal model (e. g., temporal relations such as after and before are mutually exclusive for any pair of events).
