# Paragraph Reordering

Set-Encoder is a cross-encoder architecture specifically designed for efficient and permutation-invariant paragraph reordering, particularly suitable for novelty-aware re-ranking tasks.

Set-Encoder is a cross-encoder architecture specifically designed for efficient and permutation-invariant paragraph reordering.

French text classification model based on CamemBERT architecture, specifically designed for paragraph reordering tasks in the legal domain

lightning-ir is a cross-encoder model based on the ELECTRA architecture, specifically designed for text ranking tasks. The model optimizes paragraph reordering performance through large language model distillation techniques.

A text re-ranking model based on the T5-base architecture, fine-tuned on the MS MARCO passage dataset to improve the relevance ranking of information retrieval results.