Search Results for author: Junya Takayama

Found 8 papers, 4 papers with code

DIRECT: Direct and Indirect Responses in Conversational Text Corpus

1 code implementation Findings (EMNLP) 2021 Junya Takayama, Tomoyuki Kajiwara, Yuki Arase

We create a large-scale dialogue corpus that provides pragmatic paraphrases to advance technology for understanding the underlying intentions of users.

Predicting Parking Lot Availability by Graph-to-Sequence Model: A Case Study with SmartSantander

1 code implementation21 Jun 2022 Yuya Sasaki, Junya Takayama, Juan Ramón Santana, Shohei Yamasaki, Tomoya Okuno, Makoto Onizuka

Nowadays, so as to improve services and urban areas livability, multiple smart city initiatives are being carried out throughout the world.

Graph-to-Sequence

Consistent Response Generation with Controlled Specificity

no code implementations Findings of the Association for Computational Linguistics 2020 Junya Takayama, Yuki Arase

To control the specificity of generated responses, we add the distant supervision based on the co-occurrence degree and a PMI-based word prediction mechanism to a sequence-to-sequence model.

Response Generation Specificity

Text Classification with Negative Supervision

no code implementations ACL 2020 Sora Ohashi, Junya Takayama, Tomoyuki Kajiwara, Chenhui Chu, Yuki Arase

Advanced pre-trained models for text representation have achieved state-of-the-art performance on various text classification tasks.

General Classification Semantic Similarity +4

Relevant and Informative Response Generation using Pointwise Mutual Information

no code implementations WS 2019 Junya Takayama, Yuki Arase

A sequence-to-sequence model tends to generate generic responses with little information for input utterances.

Decoder Response Generation

Dialogue-Act Prediction of Future Responses Based on Conversation History

no code implementations ACL 2019 Koji Tanaka, Junya Takayama, Yuki Arase

One significant drawback of such a neural network based approach is that the response generation process is a black-box, and how a specific response is generated is unclear.

Chatbot Response Generation

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