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Learning How to Translate North Korean through South Korean ...
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Multimodal pretraining unmasked: A meta-analysis and a unified framework of vision-and-language berts ...
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Transformer-based Lexically Constrained Headline Generation ...
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Abstract:
This paper explores a variant of automatic headline generation methods, where a generated headline is required to include a given phrase such as a company or a product name. Previous methods using Transformer-based models generate a headline including a given phrase by providing the encoder with additional information corresponding to the given phrase. However, these methods cannot always include the phrase in the generated headline. Inspired by previous RNN-based methods generating token sequences in backward and forward directions from the given phrase, we propose a simple Transformer-based method that guarantees to include the given phrase in the high-quality generated headline. We also consider a new headline generation strategy that takes advantage of the controllable generation order of Transformer. Our experiments with the Japanese News Corpus demonstrate that our methods, which are guaranteed to include the phrase in the generated headline, achieve ROUGE scores comparable to previous ... : EMNLP 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2109.07080
https://dx.doi.org/10.48550/arxiv.2109.07080
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Multimodal pretraining unmasked: A meta-analysis and a unified framework of vision-and-language berts
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In: Transactions of the Association for Computational Linguistics, 9 (2021)
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Transformer-based Lexically Constrained Headline Generation ...
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It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information ...
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It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information
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In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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Other Topics You May Also Agree or Disagree: Modeling Inter-Topic Preferences using Tweets and Matrix Factorization ...
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