Search Results for author: Kuniko Saito

Found 7 papers, 2 papers with code

InstructDoc: A Dataset for Zero-Shot Generalization of Visual Document Understanding with Instructions

1 code implementation24 Jan 2024 Ryota Tanaka, Taichi Iki, Kyosuke Nishida, Kuniko Saito, Jun Suzuki

We study the problem of completing various visual document understanding (VDU) tasks, e. g., question answering and information extraction, on real-world documents through human-written instructions.

document understanding Question Answering +1

SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images

1 code implementation12 Jan 2023 Ryota Tanaka, Kyosuke Nishida, Kosuke Nishida, Taku Hasegawa, Itsumi Saito, Kuniko Saito

Visual question answering on document images that contain textual, visual, and layout information, called document VQA, has received much attention recently.

Evidence Selection Question Answering +1

Automatically Extracting Variant-Normalization Pairs for Japanese Text Normalization

no code implementations IJCNLP 2017 Itsumi Saito, Kyosuke Nishida, Kugatsu Sadamitsu, Kuniko Saito, Junji Tomita

Social media texts, such as tweets from Twitter, contain many types of non-standard tokens, and the number of normalization approaches for handling such noisy text has been increasing.

Machine Translation Morphological Analysis

Constructing a Class-Based Lexical Dictionary using Interactive Topic Models

no code implementations LREC 2012 Kugatsu Sadamitsu, Kuniko Saito, Kenji Imamura, Yoshihiro Matsuo

This paper proposes a new method of constructing arbitrary class-based related word dictionaries on interactive topic models; we assume that each class is described by a topic.

Topic Models

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