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Register a new userAn animated picture says at least a thousand words: Selecting Gif-based Replies in Multimodal Dialog
تقول صورة متحركة ألف كلمة على الأقل: تحديد ردود GIF المستندة إلى GIF في مربع حوار MultiModal
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المحادثات عبر الإنترنت تشمل أكثر من مجرد نص.على نحو متزايد، تعمل الاستجابات القائمة على الصور مثل الميمات وحلويات الرسوم المتحركة استجابات معترف بها ثقافيا وغالبا ما تكون روح الدعابة في المحادثة.ومع ذلك، في حين أن NLP تم توسيعها إلى نماذج متعددة الوسائط، فإن أنظمة حوار المحادثة تركز إلى حد كبير على توليد الردود النصية فقط.هنا، نقدم مجموعة بيانات جديدة تبلغ 1.56 مليون محادثة Text-GIF تتحول وإدخال نموذج محادثة متعددة الوسائط جديد Pepe جمبري الملك لتحديد الردود القائمة على GIF.نوضح أن نموذجنا ينتج استجابات GIF ذات الصلة وعالية الجودة، وفي تجربة مراقبة عشوائية كبيرة ترد على المستخدمين الحقيقيين، نظين على أن ردودنا النموذجية لدينا مع صور متحركة يتم استلامها بشكل أفضل من قبل المجتمع.
Online conversations include more than just text. Increasingly, image-based responses such as memes and animated gifs serve as culturally recognized and often humorous responses in conversation. However, while NLP has broadened to multimodal models, conversational dialog systems have largely focused only on generating text replies. Here, we introduce a new dataset of 1.56M text-gif conversation turns and introduce a new multimodal conversational model Pepe the King Prawn for selecting gif-based replies. We demonstrate that our model produces relevant and high-quality gif responses and, in a large randomized control trial of multiple models replying to real users, we show that our model replies with gifs that are significantly better received by the community.
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