477 citations · 536 across the 16 of their papers we have counts for
16 papers
Focused Prefix Tuning for Controllable Text Generation
Congda Ma, Tianyu Zhao, Makoto Shing +2
In a controllable text generation dataset, there exist unannotated attributes that could provide irrelevant learning signals to models that use it for training and thus degrade the…
TACR: A Table-alignment-based Cell-selection and Reasoning Model for Hybrid Question-Answering
Jian Wu, Yicheng Xu, Yan Gao +3
Hybrid Question-Answering (HQA), which targets reasoning over tables and passages linked from table cells, has witnessed significant research in recent years. A common challenge in…
Bidirectional Transformer Reranker for Grammatical Error Correction
Ying Zhang, Hidetaka Kamigaito, Manabu Okumura
Pre-trained seq2seq models have achieved state-of-the-art results in the grammatical error correction task. However, these models still suffer from a prediction bias due to their u…
A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Naoki Kobayashi, Tsutomu Hirao, Hidetaka Kamigaito +2
To promote and further develop RST-style discourse parsing models, we need a strong baseline that can be regarded as a reference for reporting reliable experimental results. This p…
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction
Yidong Wang, Hao Wu, Ao Liu +6
Target-oriented Opinion Words Extraction (TOWE) is a fine-grained sentiment analysis task that aims to extract the corresponding opinion words of a given opinion target from the se…
Generating Repetitions with Appropriate Repeated Words
Toshiki Kawamoto, Hidetaka Kamigaito, Kotaro Funakoshi +1
A repetition is a response that repeats words in the previous speaker's utterance in a dialogue. Repetitions are essential in communication to build trust with others, as investiga…
Aspect-based Analysis of Advertising Appeals for Search Engine Advertising
Soichiro Murakami, Peinan Zhang, Sho Hoshino +3
Writing an ad text that attracts people and persuades them to click or act is essential for the success of search engine advertising. Therefore, ad creators must consider various a…
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
Bowen Zhang, Yidong Wang, Wenxin Hou +4
The recently proposed FixMatch achieved state-of-the-art results on most semi-supervised learning (SSL) benchmarks. However, like other modern SSL algorithms, FixMatch uses a pre-d…
Metric-Type Identification for Multi-Level Header Numerical Tables in Scientific Papers
Lya Hulliyyatus Suadaa, Hidetaka Kamigaito, Manabu Okumura +1
Numerical tables are widely used to present experimental results in scientific papers. For table understanding, a metric-type is essential to discriminate numbers in the tables. We…
Diverse and Non-redundant Answer Set Extraction on Community QA based on DPPs
Shogo Fujita, Tomohide Shibata, Manabu Okumura
In community-based question answering (CQA) platforms, it takes time for a user to get useful information from among many answers. Although one solution is an answer ranking method…
Pointing to Subwords for Generating Function Names in Source Code
Shogo Fujita, Hidetaka Kamigaito, Hiroya Takamura +1
We tackle the task of automatically generating a function name from source code. Existing generators face difficulties in generating low-frequency or out-of-vocabulary subwords. In…
Neural text normalization leveraging similarities of strings and sounds
Riku Kawamura, Tatsuya Aoki, Hidetaka Kamigaito +2
We propose neural models that can normalize text by considering the similarities of word strings and sounds. We experimentally compared a model that considers the similarities of b…
Syntactically Look-Ahead Attention Network for Sentence Compression
Hidetaka Kamigaito, Manabu Okumura
Sentence compression is the task of compressing a long sentence into a short one by deleting redundant words. In sequence-to-sequence (Seq2Seq) based models, the decoder unidirecti…
A Large-Scale Multi-Length Headline Corpus for Analyzing Length-Constrained Headline Generation Model Evaluation
Yuta Hitomi, Yuya Taguchi, Hideaki Tamori +5
Browsing news articles on multiple devices is now possible. The lengths of news article headlines have precise upper bounds, dictated by the size of the display of the relevant dev…
Controlling Output Length in Neural Encoder-Decoders
Yuta Kikuchi, Graham Neubig, Ryohei Sasano +2
Neural encoder-decoder models have shown great success in many sequence generation tasks. However, previous work has not investigated situations in which we would like to control t…
Applying Deep Belief Networks to Word Sense Disambiguation
Peratham Wiriyathammabhum, Boonserm Kijsirikul, Hiroya Takamura +1
In this paper, we applied a novel learning algorithm, namely, Deep Belief Networks (DBN) to word sense disambiguation (WSD). DBN is a probabilistic generative model composed of mul…