Conditional set generation using Seq2seq models. (arXiv:2205.12485v2 [cs.CL] UPDATED)

Conditional set generation learns a mapping from an input sequence of tokens
to a set. Several NLP tasks, such as entity typing and dialogue emotion
tagging, are instances of set generation. Seq2Seq models, a popular choice for
set generation, treat a set as a sequence and do not fully leverage its key
properties, namely order-invariance and cardinality. We propose a novel
algorithm for effectively sampling informative orders over the combinatorial
space of label orders. We jointly model the set cardinality …

arxiv seq2seq set