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Hideaki Takeda

National Institute of Informatics

11 papers hereh-index 284.8k citations341 works total

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

author position
  • middle author3
  • last author6

Across the 9 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.AI2
  • cs.CV2
  • cs.DB2
  • cs.SI2
affiliations
  • National Institute of Informatics
HomepageORCID 0000-0002-2909-7163
same name
  • Hideaki Takeda — 4 papers, h 2
  • Hideaki Takeda — 1 paper, h 2
  • Hideaki Takeda — 1 paper, h 1

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

activity
20152023
most citedLUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention

35 citations · 74 across the 7 of their papers we have counts for

collaborators
Showing cs.CLShow all

3 papers · 1 filter

cs.CL2020★ 35 cited

LUKE: Deep Contextualized Entity Representations with Entity-aware Self-attention

Ikuya Yamada, Akari Asai, Hiroyuki Shindo +2

Entity representations are useful in natural language tasks involving entities. In this paper, we propose new pretrained contextualized representations of words and entities based…

cs.CL2018

Wikipedia2Vec: An Efficient Toolkit for Learning and Visualizing the Embeddings of Words and Entities from Wikipedia

Ikuya Yamada, Akari Asai, Jin Sakuma +4

The embeddings of entities in a large knowledge base (e.g., Wikipedia) are highly beneficial for solving various natural language tasks that involve real world knowledge. In this p…

cs.CL2017

Learning Distributed Representations of Texts and Entities from Knowledge Base

Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda +1

We describe a neural network model that jointly learns distributed representations of texts and knowledge base (KB) entities. Given a text in the KB, we train our proposed model to…

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