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2021-04-12T12:12:04+05:30
LaTeX with hyperref
2021-04-16T01:32:46+05:30
2021-04-16T01:32:46+05:30
BERT; MLM; Self-Crtical Learning; Amazon; Advertising; Reinforcement Learning; Summarization; NLG; NLU; Generation; Natural Language Generation; Transformers; Headline
pdfTeX-1.40.21
This is pdfTeX, Version 3.14159265-2.6-1.40.21 (TeX Live 2020) kpathsea version 6.3.2
application/pdf
Yashal Shakti Kanungo
Sumit Negi
Aruna Rajan
For any E-commerce website it is a nontrivial
problem to build enduring advertisements that
attract shoppers. It is hard to pass the creative
quality bar of the website, especially at a large
scale. We thus propose a programmatic solution
to generate product advertising headlines
using retail content. We propose a state of
the art application of Reinforcement Learning
(RL) Policy gradient methods on Transformer
(Vaswani et al., 2017) based Masked Language
Models (Devlin et al., 2019). Our method creates
the advertising headline by jointly conditioning
on multiple products that a seller
wishes to advertise. We demonstrate that our
method outperforms existing Transformer and
LSTM + RL methods in overlap metrics and
quality audits. We also show that our modelgenerated
headlines outperform human submitted
headlines in terms of both grammar and
creative quality as determined by audits.
Ad Headline Generation using Self-Critical Masked Language Model
BERT
MLM
Self-Crtical Learning
Amazon
Advertising
Reinforcement Learning
Summarization
NLG
NLU
Generation
Natural Language Generation
Transformers
Headline
uuid:6e5896ab-668b-fa41-94e2-1448e32b0a67
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