28 citations · 29 across the 4 of their papers we have counts for
8 papers
Multilingual Syntax-aware Language Modeling through Dependency Tree Conversion
Shunsuke Kando, Hiroshi Noji, Yusuke Miyao
Incorporating stronger syntactic biases into neural language models (LMs) is a long-standing goal, but research in this area often focuses on modeling English text, where constitue…
Effective Batching for Recurrent Neural Network Grammars
Hiroshi Noji, Yohei Oseki
As a language model that integrates traditional symbolic operations and flexible neural representations, recurrent neural network grammars (RNNGs) have attracted great attention fr…
CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters
Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne +3
Due to the compelling improvements brought by BERT, many recent representation models adopted the Transformer architecture as their main building block, consequently inheriting the…
An Analysis of the Utility of Explicit Negative Examples to Improve the Syntactic Abilities of Neural Language Models
Hiroshi Noji, Hiroya Takamura
We explore the utilities of explicit negative examples in training neural language models. Negative examples here are incorrect words in a sentence, such as "barks" in "*The dogs b…
Learning to Select, Track, and Generate for Data-to-Text
Hayate Iso, Yui Uehara, Tatsuya Ishigaki +6
We propose a data-to-text generation model with two modules, one for tracking and the other for text generation. Our tracking module selects and keeps track of salient information…
Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation
Masashi Yoshikawa, Hiroshi Noji, Koji Mineshima +1
We propose a new domain adaptation method for Combinatory Categorial Grammar (CCG) parsing, based on the idea of automatic generation of CCG corpora exploiting cheaper resources of…