activity
20182022
most citedRemoving Word-Level Spurious Alignment between Images and Pseudo-Captions in Unsupervised Image Captioning

1 citations · 3 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL20221 cited

-gram Is Back: Residual Learning of Neural Text Generation with -gram Language Model

Huayang Li, Deng Cai, Jin Xu +1

-gram language models (LM) have been largely superseded by neural LMs as the latter exhibits better performance. However, we find that -gram models can achieve satisfactory p…

cs.CL20221 cited

Adapting to Non-Centered Languages for Zero-shot Multilingual Translation

Zhi Qu, Taro Watanabe

Multilingual neural machine translation can translate unseen language pairs during training, i.e. zero-shot translation. However, the zero-shot translation is always unstable. Alth…

cs.CL2022

Visualizing the Relationship Between Encoded Linguistic Information and Task Performance

Jiannan Xiang, Huayang Li, Defu Lian +3

Probing is popular to analyze whether linguistic information can be captured by a well-trained deep neural model, but it is hard to answer how the change of the encoded linguistic…

cs.LG2021

Transductive Data Augmentation with Relational Path Rule Mining for Knowledge Graph Embedding

Yushi Hirose, Masashi Shimbo, Taro Watanabe

For knowledge graph completion, two major types of prediction models exist: one based on graph embeddings, and the other based on relation path rule induction. They have different…

cs.CL20211 cited

Removing Word-Level Spurious Alignment between Images and Pseudo-Captions in Unsupervised Image Captioning

Ukyo Honda, Yoshitaka Ushiku, Atsushi Hashimoto +2

Unsupervised image captioning is a challenging task that aims at generating captions without the supervision of image-sentence pairs, but only with images and sentences drawn from…

cs.CL2021

User-Generated Text Corpus for Evaluating Japanese Morphological Analysis and Lexical Normalization

Shohei Higashiyama, Masao Utiyama, Taro Watanabe +1

Morphological analysis (MA) and lexical normalization (LN) are both important tasks for Japanese user-generated text (UGT). To evaluate and compare different MA/LN systems, we have…