Search Results for author: Ryo Takahashi

Found 11 papers, 4 papers with code

Are Prompt-based Models Clueless?

no code implementations ACL 2022 Pride Kavumba, Ryo Takahashi, Yusuke Oda

However, models with a task-specific head require a lot of training data, making them susceptible to learning and exploiting dataset-specific superficial cues that do not generalize to other datasets.

Language Modelling Natural Language Understanding

Two Training Strategies for Improving Relation Extraction over Universal Graph

1 code implementation EACL 2021 Qin Dai, Naoya Inoue, Ryo Takahashi, Kentaro Inui

This paper explores how the Distantly Supervised Relation Extraction (DS-RE) can benefit from the use of a Universal Graph (UG), the combination of a Knowledge Graph (KG) and a large-scale text collection.

Relation Extraction Vocal Bursts Valence Prediction

On the Subcategories of n-Torsionfree Modules and Related Modules

no code implementations12 Jan 2021 Souvik Dey, Ryo Takahashi

Let R be a commutative noetherian ring.

Commutative Algebra Representation Theory 13C60, 13D02

An Empirical Study of Contextual Data Augmentation for Japanese Zero Anaphora Resolution

no code implementations COLING 2020 Ryuto Konno, Yuichiroh Matsubayashi, Shun Kiyono, Hiroki Ouchi, Ryo Takahashi, Kentaro Inui

This study addresses two underexplored issues on CDA, that is, how to reduce the computational cost of data augmentation and how to ensure the quality of the generated data.

Data Augmentation Language Modelling +4

Word Rotator's Distance

1 code implementation EMNLP 2020 Sho Yokoi, Ryo Takahashi, Reina Akama, Jun Suzuki, Kentaro Inui

Accordingly, we propose a method that first decouples word vectors into their norm and direction, and then computes alignment-based similarity using earth mover's distance (i. e., optimal transport cost), which we refer to as word rotator's distance.

Semantic Similarity Semantic Textual Similarity +2

Data Augmentation using Random Image Cropping and Patching for Deep CNNs

1 code implementation22 Nov 2018 Ryo Takahashi, Takashi Matsubara, Kuniaki Uehara

We also confirmed that deep CNNs with RICAP achieve better results on classification tasks using CIFAR-100 and ImageNet and an image-caption retrieval task using Microsoft COCO.

Image Augmentation Image Cropping +2

A Novel Weight-Shared Multi-Stage CNN for Scale Robustness

no code implementations12 Feb 2017 Ryo Takahashi, Takashi Matsubara, Kuniaki Uehara

The proposed WSMS-Net is easily combined with existing deep CNNs such as ResNet and DenseNet and enables them to acquire robustness to object scaling.

General Classification Image Classification

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