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Found 6 papers, 1 papers with code
Generic Mechanism for Reducing Repetitions in Encoder-Decoder Models
Encoder-decoder models have been commonly used for many tasks such as machine translation and response generation.
Neural text normalization leveraging similarities of strings and sounds
We propose neural models that can normalize text by considering the similarities of word strings and sounds.
lamBERT: Language and Action Learning Using Multimodal BERT
Recently, the bidirectional encoder representations from transformers (BERT) model has attracted much attention in the field of natural language processing, owing to its high performance in language understanding-related tasks.
Controlling Contents in Data-to-Document Generation with Human-Designed Topic Labels
We propose a data-to-document generator that can easily control the contents of output texts based on a neural language model.
Generating Market Comments Referring to External Resources
Comments on a stock market often include the reason or cause of changes in stock prices, such as {``}Nikkei turns lower as yen{'}s rise hits exporters.
Distinguishing Japanese Non-standard Usages from Standard Ones
Our experimental results show that the model leveraging the context embedding outperforms other methods and provide us with findings, for example, on how to construct context embeddings and which corpus to use.
