Papers with autoregressive factorization

2 papers
Conditional set generation using Seq2seq models (2022.emnlp-main)

Copied to clipboard

Challenge: Several NLP tasks are instances of set generation.
Approach: They propose a model-independent data augmentation approach that enlarges the model with the signals of order-invariance and cardinality.
Outcome: The proposed method improves performance on four benchmark datasets with no additional annotations.
Hint-Based Training for Non-Autoregressive Machine Translation (D19-1)

Copied to clipboard

Challenge: AutoRegressive Translation models have to generate tokens sequentially during decoding and thus suffer from high inference latency.
Approach: They propose to use hidden states and word alignments to help train NART models.
Outcome: The proposed model improves on the WMT14 En-De and De-En datasets but is faster in inference than the current models.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations