Papers by Jun Goto

2 papers
Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in Conversations (2020.emnlp-main)

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Challenge: Recent research on emotion recognition in conversations (ERC) does not take self-dependency or inter-speaker dependency into account.
Approach: They propose a relational graph attention network (RGAT) model that takes speaker dependency and sequential information into account by encoding the relational Graph structure.
Outcome: The proposed model outperforms the state-of-the-art on four ERC datasets.
Label Embedding using Hierarchical Structure of Labels for Twitter Classification (D19-1)

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Challenge: Twitter is used for disaster monitoring and news material gathering . we propose a method that can consider the hierarchical structure of labels and labels themselves .
Approach: They propose a method that can consider the hierarchical structure of labels and label texts themselves.
Outcome: The proposed method outperforms the methods of the conference participants over the text REtrieval Conference (TREC) 2018 Incident Streams (IS) dataset.

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