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![DEEP LEARNING JP
[DL Papers]
http://deeplearning.jp/
Self-Motivated Communication Agent for
Real-World Vision-Dialog Navig...](https://image.slidesharecdn.com/20211029akuzawa1-211029030831/75/DL-Self-Motivated-Communication-Agent-for-Real-World-Vision-Dialog-Navigation-1-2048.jpg?cb=1668132609)
![背景
• VDNの既存研究：会話履歴の訓練データを様々な方法で利用する
• [Thomason+2020] 会話履歴をsequence-to-sequenceの方策への入力に利用
• [Roman+2020] 会話履歴で言語モデルを事前訓練 -...](https://image.slidesharecdn.com/20211029akuzawa1-211029030831/75/DL-Self-Motivated-Communication-Agent-for-Real-World-Vision-Dialog-Navigation-4-2048.jpg?cb=1668132609)
![関連研究：Cooperative Vision-and-Dialog Navigation Dataset
(CVDN) [Thomason+2020]
• CVDN：人間の対話を元にしたナビゲー
ションデータセット
• クラウドソーシングによ...](https://image.slidesharecdn.com/20211029akuzawa1-211029030831/75/DL-Self-Motivated-Communication-Agent-for-Real-World-Vision-Dialog-Navigation-5-2048.jpg?cb=1668132609)
![関連研究：HANNA [Nguyen+2019]
• HANNA：特定の位置にいくと，オラクルがサブタスク（現在地とゴールまでの中間地点へ向かう
言語指示）を教えてくれるシミュレータ環境
• 限界：特定の位置でしかオラクルとのコミュニケーション...](https://image.slidesharecdn.com/20211029akuzawa1-211029030831/75/DL-Self-Motivated-Communication-Agent-for-Real-World-Vision-Dialog-Navigation-6-2048.jpg?cb=1668132609)
![What to Ask：回答文について
• 回答スコアベクトル ：N個の質問候補について，yesかnoかで答える
• 計算方法：未来の観測情報と質問文の類似度の計算
• 例えば， Shoaled I go [Dir] to the [Obj]?...](https://image.slidesharecdn.com/20211029akuzawa1-211029030831/75/DL-Self-Motivated-Communication-Agent-for-Real-World-Vision-Dialog-Navigation-15-2048.jpg?cb=1668132609)
