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Masashi Yoshikawa

4 papers hereh-index 4147 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
same name
  • Masashi Yoshikawa — 3 papers
  • Masashi Yoshikawa — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedMultimodal Logical Inference System for Visual-Textual Entailment

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CL2019★ 1 cited

Multimodal Logical Inference System for Visual-Textual Entailment

Riko Suzuki, Hitomi Yanaka, Masashi Yoshikawa +2

A large amount of research about multimodal inference across text and vision has been recently developed to obtain visually grounded word and sentence representations. In this pape…

cs.CL2019

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…

cs.CL2018

Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference

Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji +1

In logic-based approaches to reasoning tasks such as Recognizing Textual Entailment (RTE), it is important for a system to have a large amount of knowledge data. However, there is…

cs.CL2018

Consistent CCG Parsing over Multiple Sentences for Improved Logical Reasoning

Masashi Yoshikawa, Koji Mineshima, Hiroshi Noji +1

In formal logic-based approaches to Recognizing Textual Entailment (RTE), a Combinatory Categorial Grammar (CCG) parser is used to parse input premises and hypotheses to obtain the…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.